Who We Are

Babylist is the leading registry, e-commerce, and content platform for growing families. More than 9 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, trusted guidance, and expert product recommendations for new parents and the people who love them. What began as a universal registry has grown into a full ecosystem for new parents, including the Babylist Shop, Babylist Health, and a flagship showroom in Los Angeles. Hundreds of brands in baby and beyond partner with Babylist to engage meaningfully with families during one of life’s most important transitions. With over $1 billion in annual GMV, and more than $500 million in 2024 revenue, Babylist is reshaping the $320 billion baby product industry. We’re helping parents feel confident, connected, and cared for at every step. As we build the generational brand in baby, our mission remains simple: to connect growing families with everything they need to thrive.To learn more, visit www.babylist.com.

Our Ways of Working

Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up.

What the Role Is

As a Senior Product Analyst on the Growth & LTV team, you’ll own the analytics that help Babylist understand and grow its long-term relationship with families. Your core focus is Account Foundations—the identity and navigation layer that connects registrants, gift givers, and partners across the product—and program analytics for newer businesses like Money, Health, and Education. This is where product analytics meets business performance: you’ll connect how people use Babylist to how we create lasting value over time.

Day to day, this is a mix of deep analytical work and high-leverage partnership. You’ll define how we measure success, build KPI frameworks from scratch, audit and shape our event tracking, and run experiments that inform product direction. You’ll work closely with Product, Engineering, and cross-functional leads, often being the person who brings clarity when the data is messy or incomplete. Some weeks that looks like designing an experiment; others it’s untangling identity across surfaces or connecting product behavior to revenue and cost drivers.

This is a high-autonomy role in a space that isn’t neatly defined. You’ll be working across multiple surfaces and newer business lines where the “right” answer isn’t obvious and the data isn’t always clean. If you’ve mostly operated in tightly scoped analytics roles with mature dashboards and clearly defined metrics, this will feel uncomfortable. If you prefer clean handoffs over pushing into ambiguous, cross-functional problems, this likely isn’t the right fit.

Who You Are

• 6+ years in product analytics, with advanced SQL proficiency working daily with large-scale datasets (millions to billions of rows)—you independently write complex queries, debug data issues, and validate outputs without relying on others
• Deep experience owning product analytics for consumer-facing products, with a track record of influencing product decisions through data—not just reporting on them
• Expert in event instrumentation and clickstream data, including designing tracking plans, auditing event quality, and building reliable metrics from imperfect data
• Strong experimentation background, with hands-on experience designing A/B tests, applying statistical methods, and making clear recommendations even when results are ambiguous or inconclusive
• Experience spanning both product analytics and business/program analytics, with the ability to connect user behavior to revenue, cost drivers, and LTV outcomes
• Hands-on experience with modern data tools: dbt for data modeling, Amplitude (or similar) for product analytics, LaunchDarkly (or similar) for experimentation, and Hex or Sigma for analysis and reporting
• Proven ability to prioritize across competing demands, using an impact-driven framework to decide where your time and analysis matter most
• Comfortable operating as a senior IC in a scale-up environment, owning ambiguous problem spaces end-to-end and working cross-functionally without clear playbooks
• You actively use AI tools (e.g., Claude, Cursor, Devin) in your analytical workflow—writing SQL, accelerating analysis, and improving output quality—and are excited to push how AI can expand what a single analyst can do

How You Will Make An Impact

• Own analytics end-to-end for the Growth & LTV pod, developing deep expertise in Account Foundations and program performance across Money, Health, and Education
• Build and evolve KPI trees and measurement frameworks that define how success is evaluated across user journeys and business lines
• Lead event instrumentation efforts by auditing existing tracking, identifying gaps, and partnering with Engineering to implement clean, reliable data pipelines
• Design and analyze experiments that improve engagement, retention, and long-term value, shaping product decisions through clear and actionable insights
• Connect product behavior to business outcomes by evaluating program performance across cost, revenue, and LTV drivers
• Create dashboards, reporting layers, and analytical artifacts that give teams consistent, trusted visibility into performance
• Leverage AI tools to accelerate analysis, improve code quality, and increase the scope and speed of what you can deliver as an individual contributor
• Partner closely with Product, Engineering, and cross-functional stakeholders to influence roadmap decisions and ensure data is embedded in how we build
• Contribute to the broader Data organization by raising the bar on analytical rigor and helping shape how AI is used in day-to-day analytics work

About Compensation

We use a market-based approach to compensation. The starting salary range for this role is:

USD $166,207 to $199,407
CAD $150,500 to $188,000

Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity.

Why You Will Love Working At Babylist

Our Culture

• We work with focus and intention, then step away to recharge
• We believe in exceptional management and invest in tools and opportunities to connect with colleagues
• We build products that positively impact millions of people's lives
• AI is intentionally embedded in how we work, create, and scale—supporting innovation and impact

Growth & Development

• Competitive pay and meaningful opportunities for career advancement
• We believe technology and data can solve hard problems
• We're committed to career progression and performance-based advancement

Compensation & Benefits

• Competitive salary with equity and bonus opportunities
• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

Important Notices

Recorded Interviews Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription.

Interview Integrity At Babylist, every team uses AI daily and we love it. During interviews though, we want to see you — your thinking, your problem-solving, your creativity. All interviews and assessments should be completed independently without AI tools or third-party assistance unless we tell you otherwise. We'll always be clear when AI is welcome. Misrepresentation during the process may result in removal from consideration.

Protect Yourself from Scams All official communication comes from the Babylist Talent Team via @babylist.com email addresses. We will never ask for payment, bank information, or personal financial details. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email, it's not us. Verify open roles on our careers page.

Connections at Babylist In line with our conflict of interest policy, please let us know if you have a family member or close personal relationship with a current Babylist employee. This helps us keep our process fair for everyone.

Text Message Updates You may opt in to receive SMS updates about your application. Opting out won't affect your status. Message and data rates may apply. Reply STOP to unsubscribe or HELP for assistance. See our Privacy Policy for details.

This is Engineering at Lattice

Lattice’s Engineering team is continuously working to better both our product and our craft. We use a modern, cutting-edge tech stack and love experimenting with new technologies. We strive for maintainable, robust, and performant code. We’re highly collaborative and continuously iterative and work closely with designers and product managers. We prioritize not only great technical architecture but also an amazing product experience.

As a Data Platform Engineer, you will play a pivotal role in designing and maturing Lattice’s centralized data platform — starting with a modern data lakehouse built on AWS. This is an opportunity to be a founding member of a new team, build the backbone of our data ecosystem, and directly influence the intelligence and interconnectedness of our products.

You will architect and implement foundational data infrastructure that enables scalable storage, reliable data processing, and secure access across the organization. In addition to building the lakehouse itself, you will design and maintain a set of reusable connection and query utilities that empower internal stakeholders to interact with the platform efficiently and safely.

What You Will Do

• Standardize Lattice’s data infrastructure and practices through establishing a simple, cohesive, and reliable platform that seamlessly integrates internal and partner data
• Design, develop, and deploy scalable data pipelines that can ingest, process, and serve data across multiple teams for batch and streaming workloads.
• Make data effortlessly accessible – abstract infrastructure complexity through reusable SDKs, libraries, and tooling
• Shape data governance practices ensuring access to data is secure, compliant, and high-quality. 
• Partner with Engineering, Product, and business leaders to identify data needs and implement solutions that align with strategic objectives.

What You Will Bring to the Table

• 2+ years of experience in software, data, or analytics engineering with exposure to a centralized “data platform” or large-scale data infrastructure project.
• Fluency in SQL and a general purpose programming language; Python or TypeScript preferred
• Familiarity with a data warehouse/lakehouse platform e.g. Snowflake, Redshift, BigQuery, Databricks
• Familiarity with AWS services or their equivalents e.g. IAM, Glue, Lambda, Athena, Redshift, Kinesis, EKS
• Nice to have: Hands-on experience with data processing frameworks like dbt, Spark, Kafka Streams, or Flink
• Willingness to learn and curiosity into how trustworthy, insightful data can unlock value for our users

Location Requirement:
This role is open to candidates located in British Columbia or Ontario, Canada. At this time, we are only able to hire employees residing in these provinces.

The estimated annual cash salary for this role is CAD $90,000 - CAD $120,000. This position is also eligible for incentive stock options, subject to the terms of Lattice’s applicable plans.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Life, AD&D, and Disability Insurance; Natural Disaster Support Program; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Working Remotely Stipend; One time WFH Office Set-Up Stipend; Retirement Plan; Financial Planning; and Learning & Development Budget.

Note on Pay Transparency:
Lattice provides an estimate of the compensation for roles that may be hired as required by regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

Lattice welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process.

#LI-Remote

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above. 

We are AI Native 

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.
Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

The Finance Data Team sits at the intersection of Finance & Accounting teams and Life360’s data. We provide the data ingestion / processing / reporting / egress needed by our partner teams in Finance & Accounting to enable their work and ensure SOX compliance with rigor. We push the envelope on how work is done through implementation of AI tools and capabilities to enhance our own pace of development and capabilities that we deliver to our stakeholders.

We are hiring a bar-raising Staff Data Engineer to drive our ingress / egress capabilities and build cross-cutting capabilities to drive developer experience and security. This role requires someone who can step into ambiguity, make sound architectural decisions, eliminate operational fragility, and establish an engineering discipline that others adopt.

You will serve as a technical reference point - shaping standards, influencing cross-team architecture, and driving initiatives to clear, production-ready outcomes. We value engineers who are direct, collaborative, and proactive in surfacing risks early, while helping build a team culture where high standards and psychological safety coexist.

About the Job

The Life360 Finance Data Team works as the integrator for numerous systems - bringing data into the Finance Data Warehouse, transforming it, and pushing it to its relevant destinations (reporting, data asset deliverables, tools, etc).  To support our role we are continuously building and enhancing our system - adding new data, new transformations, and new tooling to improve developer velocity and ‘buy down’ overhead costs associated with maintaining our system.

As a Staff Data Engineer you will drive forward the:

• Data ingestion suite - a mix of capabilities ranging from Fivetran to completely custom connectors that bring data into our warehouse and monitor for data quality.
• Data transformation suite - enhancing our dbt environment (dbt core) and the suite of tools that we leverage to build data models, semantic models, and other interfaces.
• Data egress suite - a mix of capabilities that allow us to push data to its end destinations.
• CI/CD pipelines and other tools / capabilities to enhance the developer experience and velocity.
• Infrastructure and networking behind our warehouse and related connectors.
• Databricks configuration and capabilities.
• Security posture and access controls.

The ideal candidate:

• They have spent years building out data platforms / infrastructure as well as creating ingress / egress data frameworks that are used in pipelines.  They have tackled numerous challenges and found novel solutions to problems for data ingestion, processing, and egress.
• They have learned how to leverage LLMs for development velocity and analytics - not just asking it to write the code but leveraging the tools to support their development under clear guidance and accepts ownership of the work produced as their own.
• They have learned to think about scalability / velocity / experience of future development and not just shipping the current project.
• They are part software engineer, part data integration engineer, and part data platform engineer.
• They adhere to the controls / procedures / separation of duties necessary to maintain our SOX compliance.

We are looking for someone with strong engineering depth who demonstrates ownership, decisiveness, and the ability to elevate both the system and the team around them.

For candidates based in the US, the salary range for this position is $190,000 to $280,500 USD. For candidates based out of Canada, the salary range for this position is $220,000 to $260,000 CAD. We take into consideration an individual's background and experience in determining final salary; therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

AI / LLM Usage

The Finance Data Team leverages LLM’s to support code generation, analysis, and other use cases.

• Cursor / Claude Code.
• Other tools (Wispr Flow, Claude & Claude Cowork, Gemini / Codex).

Your experience with AI / LLM usage should include managing code generation with a close eye on quality, standards, and testing - owning the outputs as your own.  Your work with and ability to leverage these tools will drive your velocity and ability to effectively work within our environment.

What You’ll Do

• Architect and evolve scalable data ingestion and egress frameworks and pipelines that are well tested and offer strong data quality monitoring. 
• Architect and evolve our CI/CD processes - enhancing the testing environment and observability (such as building LLM-driven reviews with context awareness through data diffing, lineage analysis / downstream impact analysis, and general context).
• Architect delivery architecture of data assets to external team partners to reduce manual operational overhead associated with month end close.
• Enhance our Claude Code / LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.
• Enhance our security posture in our AWS / Databricks environment.
• Design and implement distributed data processing systems using Spark and Databricks on AWS.
• Establish clear ingestion and integration boundaries that eliminate single points of failure.
• Proactively surface risks, dependencies, and tradeoffs before they impact delivery.
• Produce clear technical artifacts and recommendations for stakeholders and leadership.
• Design logical and physical data models balancing flexibility, performance, governance, and scalability.
• Partner closely with the Analytics Engineers on the Finance Data Team to support high-quality downstream data modeling & reporting.
• Harden pipelines with monitoring, alerting, SLAs, and recovery mechanisms.
• Mentor engineers and elevate distributed systems rigor across the team.

What We’re Looking For

• 8+ years designing and operating high-volume distributed data systems in production.
• Deep expertise with a cloud data platform (Databricks strongly preferred) and AWS from an infrastructure / services architecture, deployment, and ownership perspective.
• Strong proficiency in Python, SQL, and Spark for large-scale processing.
• Strong proficiency with modern CI/CD practices (creating GitHub Actions, writing Terraform code to manage infrastructure in Databricks / Airflow / AWS / and others).
• Hands-on experience with dbt from an infrastructure / deployment perspective and understanding of how platform decisions impact downstream modeling.
• Strong grasp of data modeling, partitioning strategies, storage formats, and analytical workload optimization.
• Experience with Airflow and data flow orchestration.
• Experience with networking challenges in data ingestion (e.g., VPC peering, firewall traversal, API rate limiting, cross-AWS account access, etc.)
• Able to effectively leverage / oversee LLM-supported code development while maintaining a high quality bar.
• Demonstrated experience with AI tools to support / enhance development - Claude Code, Cursor, etc.
• Demonstrated ability to independently scope ambiguous problems and drive them to decisive outcomes.
• Track record of proactively escalating risks and closing long-running efforts with clear recommendations.
• Experience defining ingestion validation standards and implementing data quality controls.
• Proven ability to reduce operational fragility and eliminate single points of failure.
• Strong systems design skills across distributed and event-based architectures.
• Demonstrated technical leadership influencing cross-team architectural decisions.
• Excellent communication skills across engineering, analytics, product, and executive stakeholders.
• BS in Computer Science, Engineering, Mathematics, or equivalent experience.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 

• Be a Good Person - We have a team of high-integrity people you can trust. 
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families. 
• High Intensity, High Impact - We do whatever it takes to get the job done. 

Our Commitment to Diversity

We believe that different ideas, perspectives, and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.  

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences creates a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the qualifications above, you should still seriously consider applying!

#LI-Remote

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Role Overview 

We are seeking an accomplished Principal Engineer to lead the technical architecture and evolution of our hybrid digital ecosystem. In this pivotal role, you will drive the strategic integration of multi-modal AI into our core infrastructure while architecting an omnichannel platform capable of supporting complex customer journeys. You will balance the adoption of proven third-party AI solutions (OpenAI, Anthropic) with the development of proprietary optimizations where they deliver a competitive advantage. As a technical leader, you will champion a vendor-agnostic, ethically grounded, and Privacy by Design approach to AI implementation.

Key Responsibilities

• Infrastructure Modernization: Lead the roadmap for migrating legacy data pipelines to AI-native architectures. You will design modern data orchestration solutions utilizing Apache Airflow, dbt, and Kafka to replace outdated batch processing with real-time, event-driven flows.
• AI-Native Web Transformation: Define the web infrastructure required for a high-agility ecosystem. Architect the evolution of our Headless CMS environments (AEM, Contentful) and modern frontend frameworks to enable automated page assembly and AI-driven UI components.
• Agentic Pipeline Development: Design and build autonomous pipelines that bridge the gap between design systems, automated component development, and publishing workflows.
• ML & Data Engineering Leadership: Establish standards for RAG, vector databases, and LLM orchestration. Provide architectural guidance for the seamless integration of AI capabilities across headless and omnichannel systems while ensuring consistency, performance, and security.
• Engineering Productivity: Champion the use of AI-assisted coding and engineering productivity tools such as Claude Code and Cursor to accelerate development cycles and optimize architectural decision-making.

Required Qualifications

• Experience: 8–10 years in software engineering, specializing in SaaS platform architecture and distributed systems design.
• Leadership & Advocacy: Excellence in technical diplomacy and stakeholder influence. Proven ability to translate complex AI/Data roadmaps into business value while mentoring senior teams and advocating for architectural best practices.
• Data Orchestration: Strong hands-on experience with Apache Airflow (or similar), Kafka, and dbt to support real-time AI applications.
• AI & Web Convergence: Proven expertise integrating LLMs into production web environments with a focus on agentic workflows and autonomous UI generation.
• Architectural Vision: Deep understanding of headless CMS, composable, and event-driven patterns that allow for programmatic content and UI generation.
• Modern Delivery: Experience with cloud-native technologies (AWS/GCP, Docker, Kubernetes) and a deep expertise in data privacy frameworks and AI ethics.

#LI-Hybrid

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About AlayaCare 

At AlayaCare, we’re more than just a fast-growing SaaS company, we’re a team of people passionate about transforming home healthcare. Our cloud-based platform empowers care providers around the world to deliver better outcomes for their clients.   

With 550+ employees across Canada, the US, Australia, and Brazil, we’re united by a shared mission and a strong culture of transparency, growth, and human connection. Whether you're early in your career or a seasoned expert, AlayaCare offers the opportunity to grow your impact, your skills, and your career.

About the Role

We are seeking a Staff Data Developer to join our Data & Intelligence division. Reporting to the Director of Data Engineering, you will design and implement scalable, complex data pipelines and infrastructure to power our data products.

As a senior member of the team, you’ll collaborate closely with data scientists, software engineers, and product managers to enhance the reliability and performance of our data systems, while influencing the enterprise-wide data architecture. You will also mentor junior engineers and drive best practices in data engineering.

What You’ll Do

• Design, develop, and maintain scalable, cost-effective, and reliable data pipelines for structured and unstructured data.
• Translate business needs into technical requirements and ensure alignment with product and customer success teams.
• Architect and implement data storage solutions (data lakes, warehouses, real-time processing systems) and supporting cloud infrastructure.
• Optimize pipelines for performance, scalability, cost-efficiency, and automation.
• Ensure data quality, integrity, and security across all systems.
• Evaluate and adopt new tools, technologies, and processes.
• Partner with DevOps and engineering teams for seamless deployment, monitoring, and troubleshooting.
• Document workflows and processes for knowledge sharing and maintainability.
• Stay current on industry trends in data engineering, ML, and cloud computing.
• Provide mentorship and technical leadership to junior engineers.

What You Bring to the Team

• 5+ years of hands-on experience with data software development.
• Experience with AlayaCare’s stack (Python, PHP, Vue.JS, AWS).
• Bachelor’s or advanced degree in computer science, mathematics, or related fields.
• Strong skills in DBT, SQL, Python, Snowflake, Iceberg, Spark, and AWS (ECS, S3, Aurora, RDS).
• Experience with streaming technologies such as Kafka, Kinesis, and Flink.
• Familiarity with Docker and Kubernetes.
• Expertise in dimensional data modeling and semantic layer design.
• Strong collaboration, communication, and problem-solving skills.
• Experience in Agile development methodologies.
• Mindset encouraging transparency, accountability, and trust.
• Experience in healthcare, home health, or medical devices is an asset.
• Familiarity with data governance concepts & tools is an asset.
• Bilingual in French and English is an asset.

Why Join AlayaCare?  

Work With Purpose  

At AlayaCare, you’ll help build technology that empowers care providers and improves outcomes for patients and families. Every line of code and every customer interaction contributes to making care more connected, accessible, and human.  

Grow in a High-Trust Culture  

We believe in transparency, feedback, and assuming positive intent. Here, you’ll feel safe to share your ideas and career goals, and be supported to achieve them through mentorship, career mobility, and a promote-from-within philosophy.  

Balance That Works for You  

We value flexibility and well-being. From “Wellness Fridays” to volunteer time off, to flexible vacation, we make sure you have the space to recharge, contribute to your community, and live your best life.  

Benefits That Matter  

• Equity in a well-funded, scaling company.  
• Comprehensive health benefits, telemedicine, and lifestyle spending accounts.  
• Parental leave top-up and family support programs.  

Inclusive by Design  

We celebrate diverse perspectives and foster belonging through our DEIB initiatives. Employee-led events, summits, and social activities, both in-person and virtual, create meaningful connections across our global teams.  

Location and Work Model

This role is based in Montreal. At AlayaCare, our hybrid model includes 2 set in-office collaboration days/week, and it is expected that team members are present in the office on those days to foster connection, innovation, and teamwork.  

Ready to Join Us?  

Apply today and be part of a company that makes a real difference in the future of home and community care. Not the right role for you? Share this posting with someone who might be a great fit.  

AlayaCare uses AI tools during our hiring process to support fair, consistent, and objective decision-making. Some initial screening steps may be automated to help identify qualified candidates. If your application is declined automatically, you may request a human review.  

We’re committed to creating a workplace where everyone belongs. If you require accommodation during the application process, please reach out to talentacquisitionteam@alayacare.com. 

Consensys is the leading blockchain and web3 software company founded by Joe Lubin, CEO of Consensys and Co-Founder of Ethereum. Since 2014, Consensys has been at the forefront of innovation, pioneering technological developments within the web3 ecosystem.

Through our product suite, including the MetaMask platform, Infura, Linea, Diligence, and our NFT toolkit Phosphor, we have become the trusted collaborator for users, creators, and developers on their path to build and belong in the world they want to see.

Whether building a dapp, an NFT collection, a portfolio, or a better future, the instinct to build is universal. Consensys inspires and champions the builder instinct in everyone by making web3 universally easy to use and develop on.

Our mission is to unlock the collaborative power of communities by making the decentralized web universally easy to access, use, and build on. 

You’ll get to work on the tools, infrastructure, and apps that scale these platforms to onboard one billion participants and 5 million developers. You’ll be constantly exposed to new concepts, ideas, and frameworks from your peers, and as you work on different projects — challenging you to stay at the top of your game. You’ll join a network of builders that reaches the edge of our ecosystem. Consensys alumni have moved on to become tech entrepreneurs, CEOs, and team leads at tech companies. 

About the Data Team

The Data team sits within the Office of the COO and builds the infrastructure that powers analysis across the organisation. We design, run, and optimise pipelines that bring together product, marketing, and financial data at scale. Our role is to ensure data is reliable, accessible, and ready for use—helping Consensys move fast while maintaining quality and trust.

What you’ll do

• Design, build, and maintain robust data pipelines that integrate sources across the business.
• Collaborate closely with analysts, business stakeholders, and other engineering teams to gather requirements, align timelines, discuss architecture, and ensure successful delivery.
• Document data pipelines, best practices, and processes to support onboarding and knowledge sharing within the team.
• Develop and optimize data models to deliver trusted, structured, and business-ready data.
• Ensure data quality, security, and governance are embedded in all pipelines and systems.
• Orchestrate and monitor pipeline execution to ensure reliability and scalability.
• Deploy and manage infrastructure as code.
• Build and tune big data pipelines using SQL, Python, and distributed processing frameworks.
• Work with cloud data warehouses to enable insights and analytics.
• Maintain and update reporting solutions and user dashboards.
• Automate workflows and improve CI/CD pipelines to reduce manual processes.

Would be great if you brought this to the role

• Over 6 years of experience as a Data Engineer
• Use Trusted Execution Environments (TEEs) to securely process sensitive user data, ensuring it remains protected and only aggregated insights are released.
• Strong SQL skills and experience with cloud warehouses (e.g.: Snowflake, BigQuery, Redshift).
• Hands-on experience with transformation and orchestration tools (e.g.: dbt, Airflow, Dagster).
• Comfort with Python or other scripting languages for ETL and automation.
• Familiarity with data governance and metadata management (e.g.: DataHub).
• Experience deploying and managing infrastructure as code (e.g.: Terraform, Pulumi).
• Exposure to data integration and ingestion tools (e.g.: Airbyte, Segment).
• Experience with big data and distributed processing (e.g.: Apache Spark, AWS EMR, S3).
• Exposure to open source projects
• Experience maintaining and improving reporting solutions and dashboards (e.g.: Preset/Superset, Cube.dev).
• Familiarity with CI/CD practices and automation (e.g.: GitHub Actions).
• A collaborative mindset and eagerness to work with both technical and non-technical colleagues.

Don't meet all the requirements? Don't sweat it. We’re passionate about building a diverse team of humans and as such, if you think you've got what it takes for our chaotic-but-fun, remote-friendly, start-up environment—apply anyway, detailing your relevant transferable skills in your cover letter. While we have a pretty good idea of what we need, we're ready for you to challenge our thinking on who needs to be in this role.

It is a requirement of employment in this position that applicants will be required to submit to background checks including but not limited to employment, education and criminal record checks. Further details will be provided to applicants that successfully meet the criteria for the position as determined by the company in its sole discretion. By submitting an application for employment, you are acknowledging and consenting to this requirement.

S'more about the team

As a Staff Analytics Engineer, you will be the technical architect and strategic lead for data assets driving HelloFresh’s growth globally. Data-driven decision making is at the core of our company culture and your extensive experience and knowledge across technical and business related topics will enable us to make better and faster decisions. You will work with teams across the Growth Alliance - for example Conversions, Payments, Pricing/Benefits, Communications and Adtech - by proactively identifying opportunities and building data infrastructure for insights and AI usage. You will be an influential member of the Growth Analytics team, mentoring other team members and leading the adoption of new technologies and ways of working.

Lettuce share what this role will be responsible for

• Lead Data Quality & Strategic Optimization: Act as the final authority on SQL/Python reviews and own strategic systems. You will resolve systemic deficiencies, manage non-functional requirements like global scalability, and make high-level design trade-offs in ambiguous, high-risk situations.
• Architect Robust Data Models & AI Foundations: Drive the design of scalable models and create AI-ready data foundations. You will transform data through medallion architecture (Bronze to Gold) to ensure high-quality feature engineering and "truth sets" that intuitively reflect complex business logic.
• Drive Pipeline Stewardship & Best Practices: Take ultimate accountability for pipeline reliability and define the tooling roadmap. You will lead high-impact migrations, set monitoring strategies for latency and throughput, and evangelize the adoption of new technologies like DBT and observability tools.
• Enable Cross-Functional Strategy & Mentor the Team: Partner with leadership to translate business goals into technical roadmaps while you mentor and scale the team. You will develop self-service tools for analysts and initiate organizational changes to improve delivery speed and data accuracy.
  
  
  

Sound a-peeling? Here's what we're looking for

• Leadership in Analytics Engineering & Change Agency: 7+ years of experience with a proven track record of owning technical strategy across multiple business domains. You don’t just manage the status quo; you actively simplify codebases, resolve root-cause deficiencies, and lead teams through complex migrations.
• Mastery of the Modern Data Stack & AI Proficiency: Expert-level SQL and Python skills with deep experience refactoring complex pipelines (e.g., Snowflake, dbt). You possess a strong understanding of the data lifecycle for AI and are familiar with LLM-integrated data workflows.
• Strategic Problem Solving & Exceptional Communication: Ability to solve high-complexity technical problems and anticipate bottlenecks before they hit the business. You can effectively advise Senior Leadership, bridging the gap between deep technical architecture and business value.
• Operational Excellence Mindset & Pragmatism: A focus on "metrics that matter" (P0 pipelines, MTTR, documentation) combined with the business acumen to know when to drive standards and when to adapt for optimal outcomes.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!
  
  

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

Overview

Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily.

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, high visibility role owning critical data integration pipelines and models across all of Instacart's products.

The team is still small and many of our bigger initiatives are at an early stage. We expect you to work closely with stakeholders and shape these systems from design, technical decisions, project management to execution. Your input will be critical for driving the Finance Data Strategy and building the platform that Instacart's financial data infrastructure will be built upon.

About the Job

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions.
• You are expected to mentor other team members and be a champion of engineering excellence across the organization.
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution.
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap.
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting.

About You

Minimum Qualifications

• 8+ years of working experience in a Data/Software Engineering role, with a focus on building data pipelines (specialized in financial data).
• Strong knowledge of cloud based warehouses like Snowflake, Redshift, BigQuery.
• Strong knowledge of common data infra technologies (Python, Airflow, Spark, Iceberg, Delta Lake) in a production environment.
• Expert in data modeling with experience in modeling complex financial data with scalability and usability in mind.
• Expert with SQL and dbt (Data Build Tool).
• Experience building high quality and complex ETL/ELT pipelines including pipelines for accounting/billing purposes.
• Experience with data immutability, auditability, slowly changing dimensions or similar concepts.
• Adept at fluently communicating with many cross-functional stakeholders to drive requirements and design shared datasets.
• An ability to balance a sense of urgency with shipping high quality and pragmatic solutions.
• Experience working with a large codebase on a cross functional team.

Preferred Qualifications

• Bachelor's degree in Computer Science, computer engineering, electrical engineering or equivalent work experience.
• Experience with Snowflake, dbt (Data Build Tool) and Airflow.
• Experience with SOX controlled data systems.

#LI-Remote

Overview

Our backend systems power the clients used by millions of customers every year to buy their groceries online. These systems must also support tight integration with the largest retailers in the US and Canada. Engineering at Instacart provides the opportunity to work on challenging scaling problems while also designing the features that will define our industry. You will learn how to build in an open collaborative environment serving millions of requests daily.

Finance data engineering is part of the Data Infrastructure team, working closely with accounting, billing & revenue teams to support the monthly/quarterly book close, retailer invoicing and internal/external financial reporting. The team plays a critical role in defining how financial data is modeled and standardized for uniform, reliable, timely and accurate reporting. This is a high impact, high visibility role owning critical data integration pipelines and models across all of Instacart's products.

The team is still small and many of our bigger initiatives are at an early stage. We expect you to work closely with stakeholders and shape these systems from design, technical decisions, project management to execution. Your input will be critical for driving the Finance Data Strategy and building the platform that Instacart's financial data infrastructure will be built upon.

About the Job

• You will work closely with finance, accounting, billing, and revenue teams to understand their main pain points and translate them into self-serve, reliable, and scalable data solutions.
• You are expected to mentor other team members and be a champion of engineering excellence across the organization.
• You will be part of a small team with a large amount of ownership and autonomy, managing initiatives directly from design through execution.
• You will have the freedom to suggest and drive organization-wide initiatives that shape the financial data vision and roadmap.
• You will own critical data integration pipelines and models, ensuring uniform, reliable, timely, and accurate financial reporting.

About You

Minimum Qualifications

• 8+ years of working experience in a Data/Software Engineering role, with a focus on building data pipelines (specialized in financial data).
• Strong knowledge of cloud based warehouses like Snowflake, Redshift, BigQuery.
• Strong knowledge of common data infra technologies (Python, Airflow, Spark, Iceberg, Delta Lake) in a production environment.
• Expert in data modeling with experience in modeling complex financial data with scalability and usability in mind.
• Expert with SQL and dbt (Data Build Tool).
• Experience building high quality and complex ETL/ELT pipelines including pipelines for accounting/billing purposes.
• Experience with data immutability, auditability, slowly changing dimensions or similar concepts.
• Adept at fluently communicating with many cross-functional stakeholders to drive requirements and design shared datasets.
• An ability to balance a sense of urgency with shipping high quality and pragmatic solutions.
• Experience working with a large codebase on a cross functional team.

Preferred Qualifications

• Bachelor's degree in Computer Science, computer engineering, electrical engineering or equivalent work experience.
• Experience with Snowflake, dbt (Data Build Tool) and Airflow.
• Experience with SOX controlled data systems.

#LI-Remote

Overview

Instacart’s Data Infrastructure organization builds and operates the systems that power our company’s data ecosystem, including a modern open data lakehouse on Apache Iceberg, a multi-engine compute platform for stream and analytical workloads, and self-serve tooling that helps Product, Data Science, ML, Ads, Finance, and engineering teams move fast with data.

We’re looking for a Staff Software Engineer, Data Infrastructure to join our Data Governance and Foundations Team. In this role, you’ll serve as a senior technical leader owning the architecture and delivery of our open lakehouse foundation, governance and access patterns, and multi-engine compute strategy—balancing today’s reliability with the next three to five years of scale, maturity, and cost efficiency.

You’ll collaborate closely with engineering leadership and stakeholders across Data Science, ML Platform, Ads Infrastructure, Finance Engineering, Product Engineering, and Security. You’ll operate with a high degree of ownership in a fast-paced environment where architectural decisions have real technical and financial consequences. If you thrive on complex, high-scale challenges and roll-up-your-sleeves execution, this is a chance to shape the backbone of Instacart’s data platform.

Our stack includes technologies such as Apache Iceberg, Apache Flink, Trino, ClickHouse, Apache Kafka, Apache Spark, Snowflake, Databricks, Confluent, Airflow, dbt, Delta Lake, Scala, Python, Postgres, and AWS. You’ll join a focused team of 7 engineers that values pragmatism, clarity, and impact.

About the Job

• Translate Instacart’s data strategy (e.g., monetization, federated access, real-time) into an actionable multi-year architecture roadmap; align with leadership while evolving the platform for scale, maturity, and cost efficiency.
• Own the open lakehouse foundation: define and deliver unified table formats, storage governance, and a multi-engine compute portfolio (interactive, batch, streaming) that enables portability and prevents lock-in.
• Drive real-time and streaming infrastructure for critical use cases (Ads, Fraud, ML): set deployment patterns, SLAs, and operational practices that balance performance, availability, and spend.
• Pioneer AI-native data infrastructure engineering by applying LLM/AI tools to the platform lifecycle—accelerating development, automation, observability, and cost optimization—and partnering to embed AI-powered capabilities into the platform.
• Elevate engineering excellence: lead architecture reviews, mentor senior/staff engineers, influence hiring, and clearly communicate complex trade-offs to both technical and executive audiences to ensure cross-org alignment.

About You

Minimum Qualifications

• 5+ years of software engineering experience building and operating data infrastructure or distributed systems at production scale.
• Hands-on expertise with modern data lakehouse architectures and open table formats (e.g., Apache Iceberg, Delta Lake, Hudi) and with distributed query/compute engines (e.g., Trino, Spark, ClickHouse), including performance tuning and production reliability.
• Experience with event-driven and streaming infrastructure (e.g., Kafka, Flink) for real-time pipelines and serving systems.
• Proven ownership of major platform transitions or migrations (build vs. buy, migration design, risk management) delivered to production.
• Ability to build cost/benefit and TCO models for infrastructure investments and to drive alignment via clear architecture docs and strategy memos across multiple teams and leadership levels.

Preferred Qualifications

• Experience designing platform-level governance controls and familiarity with compliance frameworks (e.g., SOX, CPRA, GDPR).
• FinOps experience optimizing data platform spend, including managing multi-million dollar infrastructure budgets and negotiating vendor contracts.
• Deep SQL proficiency and strong skills in Python or Scala for systems-level development.
• Experience with orchestration (e.g., Apache Airflow) and data transformation pipelines (e.g., dbt) in large-scale production environments.
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.

#LI-Remote

ABOUT THE ROLE

We are seeking a highly skilled and intellectually curious analyst to shape the future of financial data at Instacart, driving innovation at the intersection of systems, analytics, and business strategy.

In this role, you will architect and deliver data models, pipelines, and reporting infrastructure that empower Finance and Accounting with trusted insights at scale. 

You’ll collaborate across technical and business teams to ensure financial data is accurate, reliable, and compliant, while also advancing large-scale systems initiatives, accelerating the month-end close, and optimizing cloud spend in our AWS environment.

ABOUT THE TEAM

The Financial Data Analytics team is the connective tissue between Finance, Accounting, and Engineering. Our mission is to deliver trusted financial data that is both a foundation for compliance and a catalyst for strategic decision-making. We combine technical depth with financial expertise to build scalable, high-value data solutions—transforming complexity into clarity and empowering leaders to act with confidence.

KEY RESPONSIBILITIES

• Bridge Data & Business Needs – Translate business requirements into scalable data models by asking the right questions, digging into details, and mining insights that create measurable impact.
• Own Data Initiatives End-to-End – Take ambiguous ideas and transform them into well-defined, high-impact projects with clear deliverables.
• Build Decision-Making Tools – Design and automate dashboards, models, and reporting systems that surface clear insights and guide long-term growth strategies.
• Support Revenue Accounting – Build and maintain data products (dashboards, reports, analyses) that underpin the Revenue Accounting organization, including embedding revenue recognition logic into robust financial data models.
• Ensure Compliance & Governance – Apply compliance-first design principles to support SOX, audit readiness, and enforce data governance standards.
• Maintain Data Integrity – Implement validation, monitoring, and reconciliation frameworks to ensure accuracy, consistency, and reliability across financial datasets.
• Drive Continuous Improvement – Proactively identify opportunities for process optimization, automation, and system enhancement, unlocking efficiency across Finance and Accounting.
• Leverage AI & Next-Generation Analytics – Harness cutting-edge AI technologies (e.g., Claude, Cursor, Python ML libraries, Copilot) to reimagine how financial data is modeled, automated, and delivered—accelerating insights, scaling workflows, and shaping the future of financial analytics.

ABOUT YOU

Minimum Qualifications

• Bachelor’s degree in a related field
• 5+ years (7+ preferred) of experience in data analytics or analytics engineering roles
• Strong SQL and cloud data fundamentals, with hands-on experience in Snowflake, dbt, and BI tools (Mode, Looker, Tableau, etc.)
• Experience building and supporting complex data pipelines with emphasis on accuracy, compliance, and traceability
• Familiarity with financial data structures, accounting processes, and enterprise systems (e.g., Oracle, Workday, Salesforce, Adaptive)
• Strong communication skills with the ability to engage effectively across technical and non-technical teams

Preferred Qualifications

• Public company experience with exposure to SOX compliance
• Background in high-growth technology environments
• Experience implementing large-scale financial or operational systems (ERP, enterprise data platforms, etc.)
• Project management experience a plus
• Demonstrated ability to support Finance and Accounting teams with scalable data solutions
• Cloud cost management experience, ideally in an AWS environment
• Familiarity with AI/ML applications in data analytics (e.g., natural language SQL tools, forecasting models, anomaly detection frameworks)

#LI-Remote

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr for San Francisco, Seattle, and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Compensation

Role Description

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build, deploy, and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform, upgrading orchestration infrastructure, building shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and laying the foundation for AI-native data development. You will partner closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards, designing scalable data models, and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership, shape the technical direction of analytics infrastructure at Dropbox, and directly influence how data powers product and business decisions.

Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.

Responsibilities

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions
• Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards
• Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access
• Architect and implement a shift-left data governance strategy,  working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement
• Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS degree in Computer Science or related technical field, or equivalent technical experience
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL)
• 8+ years of Python development experience, including building and maintaining production data pipelines
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

Compensation

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

As a Data Engineer on the Mapping team, you will collaborate with our world class team of engineers, product managers, and data scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will architect, build, and maintain scalable data pipelines and services to support route simulation, experimentation, analytics, and machine learning models. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability.

Our technology stack is based on the latest technologies such as AWS, Kubernetes and Apache Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers.

Responsibilities

• Owner of the core data pipelines in mapping, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
• Develop strong subject matter expertise in the systems you manage, setting and managing SLAs for both data pipeline and datasets
• Continuously evolve data models and schemas to meet business and engineering requirements
• Develop tools that support self-service management of data pipelines (ETL), schema evolution, and perform SQL tuning to optimize data processing performance
• Write clean, well-tested, and maintainable code, prioritizing scalability and cost efficiency
• Conduct code reviews to uphold code quality standards and facilitate knowledge sharing
• Participate in on-call rotations to maintain high availability and reliability of data workflows
• Unblock, support and communicate with internal & external partners to achieve results

Experiences

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• 4+ years of relevant professional experience
• Strong experience with Spark and with a scripting language (Python, Ruby, Bash)
• Exceptional analytical skills, with an in-depth understanding of data quality issues and the ability to dive into complex datasets to resolve inconsistencies
• Excellent communication skills, with the ability to articulate technical concepts clearly to both technical and non-technical audiences while collaborating effectively across teams
• Experience with disparate database, querying and streaming technologies such as S3, DynamoDB, HDFS, Hive, Presto, Pig, HBase, Parquet, Iceberg, Flink, Spark Streaming, Kafka
• Experience with data quality tools such as Great Expectations, dbt, Monte Carlo, Soda, Collibra
• Strong understanding of SQL Engine, experience with querying geospatial data, and able to conduct advanced performance tuning
• Proficient in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
• Experience with workflow management tools (Airflow, Oozie, Azkaban, UC4, Prefect)
• Experience with infra tooling (Terraform, Cloud Formation, Docker, Kubernetes, Ansible, Chef, Puppet etc preferably in an AWS context) 
• Experience defining API schemas and developing backend services in a microservices environment

Benefits

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the Role

We’re looking for a curious, technically strong, and business-minded Data Analyst to join our Data Engineering team. This is a high-impact analytics position for someone who works at the intersection of data engineering, business intelligence, finance analytics, and AI-enabled decision support.

You’ll partner closely with Finance, Operations, Data Engineering, and business leadership to turn complex questions into trusted, actionable insights — with a particular focus on supporting the Finance organization. This role reports to the Data Engineering Manager.

What You’ll Do

• SQL & Business Analysis: Translate ambiguous business questions into precise SQL queries against our Snowflake warehouse. Own and deliver recurring financial reporting, reconciliation, and operational analytics with an eye for improving efficiency over time.
• Diagnostic & Advanced Analytics: Go beyond dashboards to explain why metrics move. Conduct root cause analyses, build forecasting models, and support decision-making through churn analysis, customer segmentation, CLV, A/B testing, and similar techniques.
• Business Intelligence & Self-Service Analytics: Build, maintain, and optimize Looker dashboards, Explores, and LookML definitions that provide governed, reliable, self-service analytics. Govern the semantic layer — metrics, dimensions, and business logic — that powers trusted reporting and AI-enabled analytics. Train business users to leverage these tools confidently.
• Finance Partnership & Compliance: Serve as the primary analytical partner to the Finance team. Own financial reporting, reconciliation, and forecasting workflows. Support SOX audits and ITAC testing, ensuring financial data is accurate, auditable, and well-documented.
• Data Quality & Cross-Functional Collaboration: Monitor and improve data quality across analytical pipelines, especially for finance-critical datasets. Gather requirements from stakeholders, translate business needs into technical specs, and collaborate with Data and Analytics Engineers to resolve upstream issues.

What You Bring

Must Have

• Experience: 3+ years in a Data Analyst, Analytics Engineer, or BI Analyst role in a modern cloud data stack environment.
• SQL mastery: Advanced SQL including CTEs, window functions, joins, and performance-aware querying in Snowflake or a comparable cloud warehouse.
• Looker expertise: Hands-on experience with Looker: dashboard development, Explores, LookML, governed metrics, and enabling self-service analytics for business users.
• dbt proficiency: Ability to read, maintain, test, and document dbt models. Familiarity with sources, tests, macros, lineage, and dbt development workflows.
• Finance domain knowledge: Solid understanding of GL, journal entries, trial balance, financial statements, reconciliations, and period-close processes. SOX/ITAC experience is highly valued.
• Data modeling: Working knowledge of dimensional modeling — fact/dimension tables, star schemas, slowly changing dimensions.
• Statistical & predictive analysis: Applied experience with regression, classification, A/B testing, segmentation, and forecasting using SQL, Python, or similar tools.
• Communication: Ability to explain complex analysis clearly to both Finance leadership and technical peers. Strong written and verbal skills.
• Version control: Comfortable with Git/GitHub: branching, PRs, and collaborative development in a terminal environment.
• AI & LLM analytics: Experience with LLMs or AI-assisted analytics tools (Claude, Gemini, GPT, Looker Conversational Analytics). Exposure to Cortex Analyst, Cortex Search, or AISQL capabilities. Understanding of MCP integration patterns is a plus.

Nice to Have

• Telecom / subscription domain: Experience in telco, connectivity, or subscription environments (MVNOs, ISPs). Familiarity with churn, ARPU, MRR, billing, and provisioning metrics.
• Workflow orchestration: Familiarity with Airflow, Dagster, or Prefect for understanding scheduled pipelines and diagnosing failures.
• Certifications: Looker, Snowflake, dbt, or cloud platform certifications.

​​The base salary range for this position is $79,650 - $88,500. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the Role

We’re looking for a curious, technically strong, and business-minded Data Analyst to join our Data Engineering team. This is a high-impact analytics position for someone who works at the intersection of data engineering, business intelligence, finance analytics, and AI-enabled decision support.

You’ll partner closely with Finance, Operations, Data Engineering, and business leadership to turn complex questions into trusted, actionable insights — with a particular focus on supporting the Finance organization. This role reports to the Data Engineering Manager.

What You’ll Do

• SQL & Business Analysis: Translate ambiguous business questions into precise SQL queries against our Snowflake warehouse. Own and deliver recurring financial reporting, reconciliation, and operational analytics with an eye for improving efficiency over time.
• Diagnostic & Advanced Analytics: Go beyond dashboards to explain why metrics move. Conduct root cause analyses, build forecasting models, and support decision-making through churn analysis, customer segmentation, CLV, A/B testing, and similar techniques.
• Business Intelligence & Self-Service Analytics: Build, maintain, and optimize Looker dashboards, Explores, and LookML definitions that provide governed, reliable, self-service analytics. Govern the semantic layer — metrics, dimensions, and business logic — that powers trusted reporting and AI-enabled analytics. Train business users to leverage these tools confidently.
• Finance Partnership & Compliance: Serve as the primary analytical partner to the Finance team. Own financial reporting, reconciliation, and forecasting workflows. Support SOX audits and ITAC testing, ensuring financial data is accurate, auditable, and well-documented.
• Data Quality & Cross-Functional Collaboration: Monitor and improve data quality across analytical pipelines, especially for finance-critical datasets. Gather requirements from stakeholders, translate business needs into technical specs, and collaborate with Data and Analytics Engineers to resolve upstream issues.

What You Bring

Must Have

• Experience: 3+ years in a Data Analyst, Analytics Engineer, or BI Analyst role in a modern cloud data stack environment.
• SQL mastery: Advanced SQL including CTEs, window functions, joins, and performance-aware querying in Snowflake or a comparable cloud warehouse.
• Looker expertise: Hands-on experience with Looker: dashboard development, Explores, LookML, governed metrics, and enabling self-service analytics for business users.
• dbt proficiency: Ability to read, maintain, test, and document dbt models. Familiarity with sources, tests, macros, lineage, and dbt development workflows.
• Finance domain knowledge: Solid understanding of GL, journal entries, trial balance, financial statements, reconciliations, and period-close processes. SOX/ITAC experience is highly valued.
• Data modeling: Working knowledge of dimensional modeling — fact/dimension tables, star schemas, slowly changing dimensions.
• Statistical & predictive analysis: Applied experience with regression, classification, A/B testing, segmentation, and forecasting using SQL, Python, or similar tools.
• Communication: Ability to explain complex analysis clearly to both Finance leadership and technical peers. Strong written and verbal skills.
• Version control: Comfortable with Git/GitHub: branching, PRs, and collaborative development in a terminal environment.
• AI & LLM analytics: Experience with LLMs or AI-assisted analytics tools (Claude, Gemini, GPT, Looker Conversational Analytics). Exposure to Cortex Analyst, Cortex Search, or AISQL capabilities. Understanding of MCP integration patterns is a plus.

Nice to Have

• Telecom / subscription domain: Experience in telco, connectivity, or subscription environments (MVNOs, ISPs). Familiarity with churn, ARPU, MRR, billing, and provisioning metrics.
• Workflow orchestration: Familiarity with Airflow, Dagster, or Prefect for understanding scheduled pipelines and diagnosing failures.
• Certifications: Looker, Snowflake, dbt, or cloud platform certifications.

​​The base salary range for this position is $79,650 - $88,500. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the opportunity

We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization. 

What You Will Be Doing

• Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
  
  
• Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
  
  
• Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
  
  
• Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
  
  
• Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
  
  
• Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
  
  
• Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
  
  
• Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.

What You Bring

• Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
  
  
• Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
  
  
• SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
  
  
• dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
  
  
• Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
  
  
• Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
  
  
• Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
  
  
• AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
  
  
• Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
  
  
• Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
  
  
• ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
  
  
• Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
  
  
• Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
  
  
• Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
  
  
• Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
  
  
• Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.

Nice to Have

• Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
  
  
• AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
  
  
• Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
  
  
• Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
  
  
• Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.

The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.

This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.

If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!

​​The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits. 

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the opportunity

We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization. 

What You Will Be Doing

• Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
  
  
• Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
  
  
• Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
  
  
• Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
  
  
• Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
  
  
• Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
  
  
• Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
  
  
• Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.

What You Bring

• Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
  
  
• Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
  
  
• SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
  
  
• dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
  
  
• Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
  
  
• Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
  
  
• Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
  
  
• AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
  
  
• Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
  
  
• Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
  
  
• ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
  
  
• Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
  
  
• Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
  
  
• Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
  
  
• Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
  
  
• Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.

Nice to Have

• Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
  
  
• AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
  
  
• Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
  
  
• Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
  
  
• Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.

The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.

This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.

If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!

​​The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits. 

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

About Clutch

Clutch is Canada’s largest online used car retailer, delivering a seamless, hassle-free car-buying experience to drivers everywhere. Customers can browse hundreds of cars from the comfort of their home, get the right one delivered to their door, and enjoy peace of mind with our 10-Day Money-Back Guarantee.
Named one of Canada’s Top Growing Companies two years in a row and awarded a spot on LinkedIn’s Top Canadian Startups list, we’re looking to add curious, hard-working, and driven individuals to our growing team.
Headquartered in Toronto, Clutch was founded in 2017. Clutch is backed by world-class investors including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca

About the role

Clutch is seeking a Senior Analytics Engineer to design, maintain, and evolve our analytics data stack. In this role, you will work closely with business teams, own critical data domains, and mentor other analytics engineers while driving data quality, governance, and modern analytics practices.

What you’ll do

• Lead the design and evolution of Clutch’s analytics data stack, including scalable ELT pipelines, dimensional models, and semantic layers using dbt, Snowflake, and Airflow

• Partner with Marketing, Product, Operations, and Finance teams to define metrics frameworks, improve reporting fidelity, and build trusted data products

• Drive best practices in data engineering: testing, observability, CI/CD, and code review for production-ready analytics code

• Own critical data domains end-to-end, ensuring models and pipelines are reliable, performant, and trusted

• Mentor and guide other analytics engineers, elevating technical practices and modeling approach

• Shape Clutch’s data governance strategy by contributing to documentation, standards, and overall data culture

• Experiment with emerging tooling in orchestration, data quality, and self-serve analytics to keep Clutch at the forefront of modern data practices

What we’re looking for

• 6–8+ years of experience in analytics engineering, data analytics, or data engineering in high-growth or fast-paced environments

• Proven track record building and maintaining complex data models with dbt in a production environment (CI, testing, documentation)

• Deep SQL expertise, with experience designing scalable dimensional models and working with large, normalized datasets

• Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift

• Experience building semantic layers and enabling self-serve BI (Looker, Sigma, Tableau)

• Strong communication skills with the ability to influence stakeholders and lead discussions around metrics and data strategy

• Strong sense of ownership, accountability, and craftsmanship for data quality, performance, and maintainability

• Experience with Python and orchestration tools (Airflow, Prefect, Dagster) for data pipelines and transformations is a plus

• Prior mentorship or leadership experience in a data team is strongly preferred

Why you’ll love it at Clutch

• Autonomy & ownership – create your own path and own your work

• Competitive compensation and equity incentives

• Generous time off program

• Health & dental benefits

Employment Type

Existing, Permanent Full-Time

Compensation & Benefits

• Salary: $120,000 - $160,000 annually 

• Equity incentives

• Comprehensive healthcare, dental, vision, prescriptions, life insurance, and dependent coverage

• Pay decisions reflect skills, performance, market benchmarking, responsibilities, and working conditions

Clutch is committed to fostering an inclusive workplace where all individuals have an opportunity to succeed. If you require accommodation at any stage of the interview process, please email talent@clutch.ca

Mercury is redefining *banking for ambitious companies and behind every great financial platform is a data system that people can actually trust.

As Mercury scales, our revenue systems generate an enormous amount of information: signals from remote and in-person meetings, automation tools, product usage, lifecycle events, and analytics pipelines. Turning that activity into clear, reliable intelligence — without brittle pipelines or constant rework — is critical to how we grow.

We’re looking for a Data Strategy & Operations leader to own the data foundations that power revenue execution. This role ensures that revenue data is reliable, interpretable, scalable, and usable as the business evolves and that teams can act on what they see with confidence.

In this role, you will report to the Head of Platforms & Infrastructure and play a central role in shaping how Mercury models, governs, and operationalizes GTM data. You’ll partner closely with Data Engineering, Data Science, Solution Architecture, Platform Engineering. etc.

*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Here are some things you’ll do on the job:

• Own the definition, structure, and reliability of data originating from revenue platforms (e.g., Salesforce, GTM tools, automation systems)
• Serve as the primary decision owner for GTM-sourced tables and views used for revenue execution, forecasting inputs, lifecycle tracking, and signal-based workflows
• Design and evolve core GTM data models across Salesforce, ETL, and analytics layers
• Partner with Data Engineering to align GTM schemas with enterprise data models and define clear data contracts between source systems and downstream consumers
• Partner with Data Science / Analytics to ensure revenue data is interpretable, statistically sound, and reflects how the business actually operates
• Own clarity around data ownership boundaries, shared dependencies, and escalation paths when upstream or downstream changes impact revenue integrity
• Define and uphold data quality, freshness, consistency, and documentation standards for revenue platforms
• Monitor and improve pipeline reliability, performance, and scalability, proactively identifying fragile or redundant transformations
• Identify opportunities to automate manual or error-prone data workflows and reduce operational overhead
• Act as a data thought partner to Platforms & Infrastructure, Revenue Operations, Analytics, and Security — advising on feasibility, tradeoffs, and sequencing for data-heavy initiatives

You Should:

• Have 7+ years of experience in data engineering or data systems roles within SaaS or technology companies
• Have deep experience designing and operating production data pipelines
• Be highly proficient in SQL and experienced in data modeling
• Have hands-on experience with modern data stacks (e.g., Snowflake, BigQuery, Redshift)
• Have experience with ETL / ELT tooling (e.g., dbt, Airflow, Census, or similar)
• Understand Salesforce data models and common GTM system architectures
• Be able to translate business concepts into durable, well-structured data models
• Communicate clearly with both technical and non-technical partners

Preferred:

• Experience supporting revenue, sales, or customer lifecycle data
• Familiarity with event-based data platforms (e.g., Data Cloud or equivalents)
• Experience working alongside platform engineering and security teams
• Exposure to data governance, access controls, and compliance considerations
• Experience mentoring or guiding other data practitioners

Compensation:

The total rewards package at Mercury includes base salary, equity, and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $158,400 - $198,000
• US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $142,600 - $178,200
• Canadian employees (any location): $149,700 - 187,100 CAD

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.] 

#LI-SN1

Opportunité 

À Valtech, vous trouverez un environnement propice à l’apprentissage continu, à l’impact concret et à la croissance professionnelle. Que vous développiez de nouvelles solutions digitales, remettiez en question les idées reçues ou construisiez la prochaine génération d’expériences client, votre travail contribuera à transformer les secteurs d'activité. 

Nous sommes fiers de: 

• Notre travail et l'innovation que nous encourageons 
• Nos valeurs : « share, dare, care » 
• Une culture d'entreprise qui favorise la créativité, la diversité et l'autonomie 
• Notre structure mondiale sans frontières, qui permet une collaboration fluide 

La maîtrise de l'anglais est requise, car le rôle implique des communications régulières avec des clients et des collègues situés à l'extérieur du Québec.

Rôle 

Veuillez noter que nous acceptons uniquement les candidatures provenant des provinces de l’Ontario, de la Colombie-Britannique (Vancouver) et du Québec pour ce poste. Pour les candidats basés au Québec, une maîtrise de l’anglais est nécessaire, car le poste implique une collaboration avec des équipes situées dans le reste des Amériques et occasionnellement en Europe.

Nous recherchons un(e) Architecte de données principal(e) (niveau Principal) possédant une solide expertise en architecture de données d’entreprise, en habilitation de l’IA et en paradigmes de développement cloud-native. Ce rôle va au-delà de l’ingénierie pratique : il requiert un(e) leader capable de définir la stratégie de plateforme, la posture de sécurité, d’influencer des clients de haut niveau et d’accompagner des équipes sur plusieurs programmes menés en parallèle.

En plus de solides compétences sur Microsoft Fabric et Azure, le/la candidat(e) idéal(e) possède une expérience sur AWS ou GCP, ainsi qu’avec Databricks, et une compréhension globale des architectures de données modernes. Il/elle doit être à l’aise pour soutenir les démarches commerciales, porter la vision architecturale et garantir l’intégrité technique des solutions tout au long de leur mise en œuvre.

Afin de gérer efficacement ce projet et son écosystème, le/la candidat(e) idéal(e) démontre une expertise pratique avérée en SQL, Python, systèmes distribués, gouvernance des données et architecture cloud. Il/elle doit être à l’aise pour accompagner les clients, cadrer et résoudre les écarts architecturaux afin de répondre aux exigences des solutions, et définir une stratégie à long terme en matière de données et d’intelligence artificielle.

Responsabilités du poste

Architecture et stratégie

• Concevoir et piloter des architectures de données complexes à l’échelle de l’entreprise sur MS Fabric, Azure, GCP, AWS ou dans des environnements Databricks (serverless ou hébergés).
• Définir et faire respecter les standards architecturaux, les modèles et les cadres de gouvernance couvrant l’ingestion, la modélisation, la traçabilité (lineage), la sécurité et l’orchestration.
• Structurer des approches architecturales intégrant l’IA, incluant les fondations de données pour le ML, le feature engineering et des pipelines d’opérationnalisation à faible latence.
• Agir en tant que conseiller(ère) principal(e) auprès des responsables techniques côté client afin de définir la stratégie à long terme, les feuilles de route et les initiatives de modernisation.
• Diriger l’orientation architecturale lors des phases d’avant-vente, incluant la conception de solutions, le cadrage, l’estimation et les présentations auprès des instances dirigeantes.
• Anticiper les impacts en aval des décisions architecturales ; conserver la responsabilité lorsque les équipes de delivery ou certaines contraintes nécessitent des écarts par rapport à la conception initiale.

Leadership en ingénierie des données

• Concevoir des pipelines de données hautement disponibles, distribués et tolérants aux pannes, supportant des charges de travail batch et streaming.
• Superviser la migration et l’intégration de sources de données complexes et hétérogènes vers des plateformes Fabric, Azure, GCP ou Databricks.
• Définir des modèles de type medallion/lakehouse (zones Bronze/Silver/Gold) ou leurs équivalents cloud.
• Établir des standards d’entreprise pour les couches ingestion → transformation → exposition (serving) dans des environnements multi-cloud.
• Optimiser les performances des traitements de données à grande échelle sur Spark, Databricks et les moteurs natifs de Fabric.
• Assurer le leadership sur 2 à 3 projets simultanés avec une allocation variable, en garantissant la cohérence architecturale et la qualité de livraison, tout en contribuant à des travaux techniques approfondis lorsque nécessaire.

Exécution technique et contribution pratique

• Développer des transformations avancées, des pipelines et des frameworks en utilisant SQL, Python, dbt et les outils cloud-native de Fabric/Databricks.
• Mettre en œuvre l’automatisation via des API REST, Data Factory, des services d’orchestration et des outils de workflows multi-cloud.
• Encadrer les ingénieur(e)s sur l’architecture distribuée, la conception des métadonnées, les cadres de qualité des données et les bonnes pratiques de gestion de plateforme.
• Réaliser des analyses de causes racines sur des problématiques complexes de plateforme ou de performance, et mettre en place des remédiations durables et évolutives.

Collaboration et influence

• Agir en tant que principale autorité technique lors des revues d’architecture, de la conception de solutions et de la planification transversale.
• Conduire des échanges stratégiques avec des parties prenantes de niveau direction et exécutif.
• Traduire des architectures complexes en impacts métiers clairs pour des audiences non techniques.
• Encadrer les équipes d’ingénierie, les architectes techniques, les chefs de projet et les architectes juniors afin de renforcer les capacités organisationnelles.
• Représenter l’architecture lors des échanges d’avant-vente, des présentations de capacités et des cycles de propositions.

Qualifications requises 

Afin d’être éligible à ce poste, vous devez posséder les qualifications essentielles suivantes: 

• Plus de 10 ans d’expérience en ingénierie des données, architecture de données ou ingénierie de plateformes.
• Expérience dans la conception ou la mise en place de plateformes de données d’entreprise sur au moins l’un des environnements suivants : Azure, GCP ou AWS, ainsi que Databricks.
• Expertise approfondie en SQL, Python, traitement distribué des données et conception de données cloud-native.
• Expérience significative avec les modèles d’architecture medallion/lakehouse.
• Solide connaissance des plateformes de données modernes : Databricks, Azure Synapse, Microsoft Fabric, Delta Lake, BigQuery, etc.
• Expérience avérée dans la direction architecturale de grands programmes et de plusieurs projets menés en parallèle.
• Expérience en automatisation et intégration d’entreprise via des API REST.
• Excellentes compétences en communication et capacité à interagir avec assurance auprès de la direction et des clients.
• Expérience en avant-vente, en conception de solutions techniques ou en leadership architectural orienté client.

Qualifications souhaitées

• Maîtrise des outils de reporting Tableau, Power BI et Microsoft Fabric.
• Expérience dans la conception d’architectures de données intégrant l’IA et de pipelines de données pour le machine learning.
• Expérience démontrée dans la définition et la mise en œuvre des meilleures pratiques DevOps.
• Expérience avec Spark, Hive, Impala et autres frameworks Big Data.
• Connaissance des composants d’architectures multi-cloud (Azure, GCP, AWS).
• Expérience avec des outils d’automatisation de pipelines tels qu’Airflow, Azure Data Factory et Prefect.
• Expérience dans la direction d’équipes techniques et la gestion de projets data / analytics / machine learning.
• Maîtrise des stacks applicatives front-end et back-end ainsi que de la conception d’API (REST/GraphQL).

Si vous ne possédez pas toutes les qualifications mentionnées ou si vous avez des lacunes dans votre parcours, nous vous encourageons à postuler. À Valtech, nous reconnaissons la richesse des talents et valorisons la pluralité des perspectives ainsi que la soif d’apprendre. 

Engagement pour l’inclusion 

Nous concevons des expériences qui conviennent à toutes les personnes — et cela commence par nos équipes. À Valtech, nous avons à cœur de bâtir une culture inclusive où chaque individu se sent soutenu pour grandir, s'épanouir et atteindre ses objectifs. Quel que soit votre parcours, vous avez votre place. Explorez notre site Diversité et Inclusion pour en savoir plus sur nos actions en faveur d’un Valtech plus équitable. 

Bénéfices et avantages 

Il s’agit d’un poste en temps plein basé à Québec, Canada.

Valtech offre un programme d’avantages sociaux complet, en vigueur après trois mois de service continu :

• Un régime d’assurance complet, avec la possibilité de choisir le module qui répond le mieux à vos besoins — Or, Argent ou Bronze. Selon le module sélectionné, l’employeur peut contribuer jusqu’à 80 % de votre couverture. Ce régime comprend des assurances invalidité de courte et de longue durée.
• Dialogue via Sun Life vous donne accès à des services de soins de santé virtuels, vous permettant de consulter un professionnel de la santé pour des urgences, des renouvellements d’ordonnance, et plus encore. Vous avez également accès au Programme d’aide aux employés et à leur famille, ainsi qu’à un programme complet de soutien en santé mentale.
• Un Compte de dépenses personnel de $500, pouvant être utilisé pour des remboursements de soins de santé, des abonnements au gym, des passes de transport en commun, des fournitures de bureau ou des contributions à votre REER par l’intermédiaire de Valtech.
• Un régime de retraite dans lequel Valtech égalera 100% de vos contributions à votre REER par l’entremise d’un Régime de participation différée aux bénéfices (RPDB), jusqu’à un maximum de 4 %. Vous pouvez commencer à cotiser à votre REER immédiatement, et au RPDB après 3 mois. L’acquisition des droits du RPDB est complétée après 24 mois de service.
• L’accès à un programme de vacances flexibles selon la politique de Valtech pour soutenir votre équilibre travail-vie personnelle, comprenant 5 jours disponibles pendant votre période de probation et un montant au prorata pour le reste de l’année.
• Un remboursement de technologie personnelle — $30/mois offert à chaque employé dès le premier jour.
• Nous fermons durant les vacances d’hiver et offrons des horaires flexibles tout au long de l’année, afin que vous puissiez profiter des après-midi ensoleillées du vendredi — pourvu que vos heures hebdomadaires soient complétées.

Processus de recrutement 

Une fois votre candidature envoyée, notre équipe Talent Acquisition l’examinera sous quelques jours. Si vos compétences et votre expérience correspondent au poste, nous vous contacterons pour les prochaines étapes. 

⚠️  Attention aux fraudes : n’interagissez qu’avec des adresses e-mail officielles se terminant par @valtech.com. 

Nous nous engageons en faveur de l’inclusion et de l’accessibilité. Si vous avez besoin d’un aménagement raisonnable pendant le processus de recrutement, veuillez l’indiquer dans votre candidature ou en informer votre Talent Partner. 

À propos de Valtech 

Valtech est une entreprise d’innovation et d’expérience qui a pour vocation d’offrir une meilleure façon d'appréhender le monde. En combinant expertises, secteurs et cultures, nous aidons les marques à créer de la valeur dans un monde de plus en plus digital. 

À l’intersection des données, de l’IA, de la créativité et de la technologie, nous accompagnons la transformation de grandes entreprises telles que L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, et bien d’autres. 

À Valtech, la transformation ne se limite pas aux discours. Nous la concrétisons. Nos collaborateurs sont au cœur de notre succès, et nous cultivons un environnement où chaque talent peut s’épanouir, évoluer et innover. 

Prêt·e à imaginer la suite ? Rejoignez-nous. 

Conformément à la loi allemande sur l'égalité de traitement et à son équivalent français, les offres d'emploi doivent être publiées de manière non sexiste. Nous utilisons la mention pour préciser que ce poste est ouvert à tous les genres dans ces pays, même si le titre du poste lui-même peut être traduit ou interprété comme « masculin » en allemand ou en français. 

What is The Role

Our Marketing organization is building an AI-powered intelligence system to drive strategy, insights, and revenue. We are looking for a Principal Analytics Engineer to lead the design and build of this foundation. This role is about more than just writing code—it’s about creating the semantic blueprint for how Elastic understands and interacts with its business data.

You will synthesize complex data streams into a unified, high-fidelity system that serves as the "source of truth" for the entire customer journey. By engineering a structured knowledge layer, you will enable Elastic to scale Go-To-Market (GTM) efforts in a world where data must be optimized for human reporting, predictive science, and conversational AI alike.

What You Will Be Doing

• Architect the Foundation: Design and build the core BigQuery and dbt infrastructure that powers Elastic’s marketing intelligence, transforming raw signals into high-fidelity, agent-ready data products.
• Enable AI & Agents: Develop the semantic layer and structured knowledge base that allows AI agents to accurately "talk" to our business data and reason through complex performance questions.
• Map the Journey: Integrate disparate signals across digital, product, and sales into a unified lifecycle model that tracks the customer’s path from discovery to revenue.
• Scale through Partnerships: Partner with Enterprise, Product, Sales, and Finance teams to align on shared metrics while mentoring other engineers to uphold high standards for our data foundation.

What You Bring

• Data-as-a-Product: You treat data as a high-value product. You are dedicated to the user experience of data—ensuring it is discoverable and reliable for both human teammates and AI agents.
• Technical Proficiency: Deep experience with BigQuery, dbt, and semantic layers (e.g., dbt Semantic Layer, Vortex AI). You have a proven ability to apply automation or LLM-assisted workflows to the data modeling lifecycle.
• Architectural Design: Ability to build complex, interconnected systems by starting with the desired outcome and working backward. You enjoy creating extensible frameworks that empower others to innovate.
• Systems & Design Thinking: The ability to look at a complex web of data and see the underlying architecture required to make it simple and extensible.
• Collaborative Communication: A track record of "translating" technical debt into business value and coaching peers through complex architectural hurdles.
• Operational Excellence & Governance: You treat data as infrastructure. You have deep experience implementing data contracts, automated quality monitoring (DQM), and governance frameworks that ensure metrics remain consistent, secure, and reliable across the enterprise.

Bonus Points

• GTM Fluency: A strong understanding of Go-To-Market mechanics—knowing how technical data structures translate into business-critical concepts like customer acquisition, attribution, and revenue.
• Marketing Science Foundations: Familiarity with Marketing Mix Modeling (MMM), causality, or incrementality analysis to help the business understand the true ROI of different channels.
• Privacy & Ethics: Understanding of GDPR/CCPA compliance and how to manage data privacy and consent within a marketing stack, especially when training AI models.
• Identity Resolution: Proven experience with Identity Stitching or Customer 360 frameworks to unify anonymous digital signals with known customer records.
• AI Production Scaling: Experience moving AI models or agentic workflows from experimental pilots into standardized, production-level deployments.

#LI-JM5

About the Job

At BuildOps, we’re building a groundbreaking software solution designed to empower today’s commercial contractors. From service management to project execution, we’re reimagining how our customers operate. Our team thrives on ambition, innovation, and collaboration—qualities we look for in every new hire.

As the Manager, Data Architects – Professional Services, you’ll own the data architecture and migration strategy that underpins BuildOps implementations, reporting, and long-term customer success. You’ll lead a team of Data Architects responsible for data discoveries, migration plans and cutovers, reporting packages, and complex ETL projects—shaping how data flows across our most strategic customers.

What You’ll Do

• Lead, coach, and develop a high-performing team of Data Architects; own hiring, onboarding, performance, and career growth.
• Own the end-to-end data architecture for implementations, including core data models, source-system mapping patterns, and standards for staging, validation, and reporting.
• Define and maintain reference architectures and reusable playbooks for migration and reporting scenarios (e.g., ServiceTitan, SAMPro, QuickBooks, Intacct, NetSuite, Vista).
• Set strategy and standards for data discovery, mapping, transformation, validation, and cutover; enforce data quality thresholds for go-live.
• Partner with Implementation, Solutions Architecture, Integrations, and Product & Engineering to translate business/reporting needs into concrete data designs.
• Design and roll out SOPs, tools, and documentation that make data work scalable, predictable, and easy for the broader PS org to leverage.
• Own data delivery planning and capacity across implementations; track throughput, quality, and rework, and proactively flag risks and mitigation options.

What We Look For

Required

• 7+ years in data architecture, data engineering, or advanced analytics, including hands-on experience with data modeling, ETL/ELT, and BI/reporting.
• 3+ years managing data-focused teams (analysts, architects, engineers, or similar) with a track record of building high-performing teams.
• Strong practical experience with relational data modeling and multiple source systems (FSM, ERP, accounting, CRM, etc.).
• Proven success leading data migration or large-scale data initiatives in SaaS implementations or enterprise programs.
• Excellent communication and documentation skills; able to explain complex data concepts to non-technical stakeholders.
• Systems-thinking mindset with a bias toward pragmatic, repeatable solutions over one-off custom work.

Preferred

• Experience with commercial mechanical, electrical, plumbing, HVAC, or similar contracting businesses.
• Hands-on experience with accounting/ERP systems (e.g., QuickBooks, Sage Intacct, NetSuite, Vista, Spectrum).
• Familiarity with modern data tooling (SQL warehouses, ETL/ELT platforms, dbt, BI tools) and integration patterns.
• Experience in B2B SaaS, especially in Professional Services, implementations, or customer success.
• Experience building or contributing to internal tooling for data mapping, validation, or bulk operations.

Who You Are

• A people-first leader who can set clear strategy and dive into details when needed.
• Comfortable owning complex, cross-functional programs that touch implementations, integrations, and analytics.
• Pragmatic, structured, and focused on creating scalable patterns rather than bespoke solutions.
• A strong communicator who can align technical and non-technical stakeholders, even under pressure or tight timelines.

Compensation

• Raleigh: $138,000 - $172,000 base + annual bonus opportunity 
• Toronto: 107,000 - 134,000 CAD base + annual bonus opportunity 

About the Finance team 

The Finance team ensures Affirm remains financially sound and strategically positioned for growth. Our team manages financial planning, accounting, pricing, vendor management, tax, investor relations, and corporate development. We deliver timely insights, accurate reporting, and careful analysis to support decision-making. From day-to-day financial operations to major investments, we enable sustainable, informed growth by maintaining strong fiscal discipline.

About the team

Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building and scaling a single source of truth for financial information using dbt and Snowflake to enable scalable BI, close workflows, controls, and automation across the org.

We’re looking for a Staff Analytics Engineer to build and own our Financial Subledger Data Platform—the canonical set of dbt models, governed datasets, and control frameworks that transform operational/ledger events into trusted, explainable, accounting-ready outputs. This is a senior hands-on role: you will write and ship production dbt code yourself (models, tests, docs), set standards for the platform, and directly manage and mentor one Analytics Engineer as a player/coach. This role operates with high autonomy and significant cross-functional partnership across Accounting, Financial Reporting, Financial Systems, and upstream product engineering teams.

We want someone who can maintain and harden today’s platform while also giving us flexibility to adopt new technologies (e.g., evolving warehouse patterns, new table formats, catalog/governance tooling, orchestration approaches) as our subledger and control needs scale.

What you’ll do

• Build and own dbt models for the financial subledger platform (staging → intermediate → canonical facts/balances/marts → semantic), including naming conventions, macros, and reusable patterns.
• Implement strong data quality and controls in dbt: tests (unit/relationship/assertions), freshness, anomaly checks, and automated reconciliations that support close and audit readiness.
• Embed AI-assisted reconciliation capabilities into the platform (within appropriate security/controls guardrails): automate variance triage, suggest likely root causes, and generate human-reviewable reconciliation narratives and evidence artifacts.
• Own end-to-end subledger data products (e.g., event/fact layers, balance rollforwards, reconciliation outputs) with traceability from source events through transformations to reporting outputs.
• Partner with Accounting/Financial Reporting to translate requirements into clear model specifications (definitions, posting logic assumptions, tie-out rules) and ship them as durable dbt assets.
• Drive production operational ownership: monitoring/alerting, incident response, root-cause fixes, and release hygiene for the pipelines and models you own.
• Collaborate with upstream engineering teams to define inputs and improve source data quality via contracts and change management.
• Coach and develop one Analytics Engineer (Poland) via code review, pairing, scoped ownership, and clear technical direction.

What we look for

• Deep, hands-on analytics engineering experience: you have built and maintained production dbt projects (models, tests, macros, documentation, CI) and can own them end-to-end.
• Strong SQL and data modeling skills; experience building canonical datasets that support finance reporting, reconciliations, or other correctness-critical outcomes.
• Experience operating data pipelines in a warehouse environment (Snowflake preferred): performance tuning, cost awareness, and reliability practices.
• Strong programming skills (Python preferred) for building data tooling and automation (e.g., control checks, reconciliation workflows, utilities, CLIs, and integrations).
• Deep Snowflake technical expertise: architecture patterns (micro-partitioning/clustering, query optimization), security/governance (RBAC, masking policies), and operational excellence (monitoring, cost management, reliability).
• Strong ownership mindset and ability to lead ambiguous work through influence across Finance, Accounting, and Engineering stakeholders.
• Nice to have:
  • Experience with accounting concepts (subledgers, journal entries/posting logic, balance rollforwards, tie-outs, close processes).
  • Experience designing SOX-friendly controls and producing repeatable evidence from data pipelines.
  • Experience applying AI/LLMs to data quality or reconciliation workflows (e.g., anomaly explanation, automated investigation summaries), with strong governance and human-in-the-loop review.
  • AWS experience (nice to have): S3/IAM, data platform primitives, and cloud architecture concepts that support secure, reliable data products.

Base Pay Grade - O
Equity Grade - 6

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

CAN base pay range per year: $170,000 - $220,000

#LI-Remote

About the Finance team 

The Finance team ensures Affirm remains financially sound and strategically positioned for growth. Our team manages financial planning, accounting, pricing, vendor management, tax, investor relations, and corporate development. We deliver timely insights, accurate reporting, and careful analysis to support decision-making. From day-to-day financial operations to major investments, we enable sustainable, informed growth by maintaining strong fiscal discipline.

About the team

Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building and scaling a single source of truth for financial information using dbt and Snowflake to enable scalable BI, close workflows, controls, and automation across the org.

We’re looking for a Staff Analytics Engineer to build and own our Financial Subledger Data Platform—the canonical set of dbt models, governed datasets, and control frameworks that transform operational/ledger events into trusted, explainable, accounting-ready outputs. This is a senior hands-on role: you will write and ship production dbt code yourself (models, tests, docs), set standards for the platform, and directly manage and mentor one Analytics Engineer as a player/coach. This role operates with high autonomy and significant cross-functional partnership across Accounting, Financial Reporting, Financial Systems, and upstream product engineering teams.

We want someone who can maintain and harden today’s platform while also giving us flexibility to adopt new technologies (e.g., evolving warehouse patterns, new table formats, catalog/governance tooling, orchestration approaches) as our subledger and control needs scale.

What you’ll do

• Build and own dbt models for the financial subledger platform (staging → intermediate → canonical facts/balances/marts → semantic), including naming conventions, macros, and reusable patterns.
• Implement strong data quality and controls in dbt: tests (unit/relationship/assertions), freshness, anomaly checks, and automated reconciliations that support close and audit readiness.
• Embed AI-assisted reconciliation capabilities into the platform (within appropriate security/controls guardrails): automate variance triage, suggest likely root causes, and generate human-reviewable reconciliation narratives and evidence artifacts.
• Own end-to-end subledger data products (e.g., event/fact layers, balance rollforwards, reconciliation outputs) with traceability from source events through transformations to reporting outputs.
• Partner with Accounting/Financial Reporting to translate requirements into clear model specifications (definitions, posting logic assumptions, tie-out rules) and ship them as durable dbt assets.
• Drive production operational ownership: monitoring/alerting, incident response, root-cause fixes, and release hygiene for the pipelines and models you own.
• Collaborate with upstream engineering teams to define inputs and improve source data quality via contracts and change management.
• Coach and develop one Analytics Engineer (Poland) via code review, pairing, scoped ownership, and clear technical direction.

What we look for

• Deep, hands-on analytics engineering experience: you have built and maintained production dbt projects (models, tests, macros, documentation, CI) and can own them end-to-end.
• Strong SQL and data modeling skills; experience building canonical datasets that support finance reporting, reconciliations, or other correctness-critical outcomes.
• Experience operating data pipelines in a warehouse environment (Snowflake preferred): performance tuning, cost awareness, and reliability practices.
• Strong programming skills (Python preferred) for building data tooling and automation (e.g., control checks, reconciliation workflows, utilities, CLIs, and integrations).
• Deep Snowflake technical expertise: architecture patterns (micro-partitioning/clustering, query optimization), security/governance (RBAC, masking policies), and operational excellence (monitoring, cost management, reliability).
• Strong ownership mindset and ability to lead ambiguous work through influence across Finance, Accounting, and Engineering stakeholders.
• Nice to have:
  • Experience with accounting concepts (subledgers, journal entries/posting logic, balance rollforwards, tie-outs, close processes).
  • Experience designing SOX-friendly controls and producing repeatable evidence from data pipelines.
  • Experience applying AI/LLMs to data quality or reconciliation workflows (e.g., anomaly explanation, automated investigation summaries), with strong governance and human-in-the-loop review.
  • AWS experience (nice to have): S3/IAM, data platform primitives, and cloud architecture concepts that support secure, reliable data products.

About the Role:

• Build and ship high quality applications to optimize in store operations and decision making.
• Collaborate with your engineering teammates to support thousands of grocery stores critical fresh food supply chains across the US.
• Working closely with product managers, designers, and our users, deliver great product experiences across the iPad, the web front-end, API, and data layers.
• Participate in and provide meaningful feedback about major design choices.
• Build out our analytics and monitoring/observability to understand our system behavior and make informed decisions.
• Ensure the quality of our software via automated tests
• Design and build UIs, APIs, and solutions that are reusable and extensible.
• Work alongside machine learning specialists to drive new feature development.

Skills and Experience

The following represents attributes our ideal candidate possesses. We encourage all highly qualified candidates to apply, even if they do not fulfill all the listed criteria.

• BS in Computer Science or equivalent experience
• 2+ years experience with full-stack web development, including some web front-end and API development
• Experience building & maintaining production level APIs and applications
• Collaborative attitude while also being highly self-directed
• Strong problem solving skills and excitement to tackle hard problems
• Enjoy working in a fast-paced, startup environment
• Required skills: TypeScript (or Javascript), React, and Python
• Nice-to-have skills: PostgreSQL, GraphQL, Databricks, DBT, Terraform/OpenTofu, Azure, pair programming, test-driven development

This position is not eligible for company sponsorship. 

Salary Range in Canada.: $136,000 - $205,000 (CAD)

The Role

AI is no longer a roadmap item — it's the operating system for how modern growth teams win. We're hiring a AI Native Engineer, Growth Marketing to be the hands-on builder who embeds AI into every corner of how our Growth team works: performance marketing, creative production, CRM, landing pages, growth ops, and beyond.

This is a rare hybrid role. You're equal parts engineer and growth practitioner — someone who can write a Python script in the morning, ship a Braze-connected AI workflow by afternoon, and explain the business impact to a non-technical stakeholder by EOD. You don't need to have done this at scale before — you need to be obsessed with building at the frontier of what's possible and have the technical chops to make it real.

You'll report directly to the Head of Growth and work across every subteam in the Growth org as their embedded AI engineer.

Responsibilities:

• Performance Marketing: Build AI-powered tools to automate bid strategy analysis, budget pacing alerts, creative performance scoring, and anomaly detection across paid channels (SEM, Meta, Affiliate, YouTube, etc.)
• Creative Studio: Develop AI workflows for ad copy generation, creative brief automation, image asset variation at scale, and creative performance feedback loops between analytics and the studio team
• CRM & Lifecycle: Implement AI-driven personalization and send-time optimization across email, SMS, push, and in-app channels; build agentic workflows that pull Snowflake data, generate segment logic, and trigger Braze campaigns with minimal manual intervention
• Landing Pages & Conversion: Automate LP variant generation, headline testing ideation, and personalization logic by audience segment or traffic source
• Growth Ops: Build internal AI tools — dashboards, Slack bots, report generators — that reduce repetitive analytical work and accelerate decision-making across the team
• Growth Product: Partner with Product and Engineering to identify where AI-powered features (recommendations, dynamic content, smart nudges) can accelerate funnel conversion and retention
• Tooling & Infrastructure: Evaluate, implement, and maintain the AI/ML toolstack that powers Growth — from LLM APIs to workflow orchestration tools to data pipelines

What Success Looks Like

• A measurable reduction in manual hours across mundane Growth through AI-driven automation
• At least 5-10 production-grade AI tools or workflows live and actively used by the team within the first 4 months
• CRM campaigns that are more personalized, faster to launch, and higher-performing because of AI assist
• Creative output volume increases without a proportional increase in headcount
• The Growth team thinks of you first when they want to do something smarter, faster, or at scale

Qualifications:

• 2–5 years of engineering or technical experience, with meaningful hands-on work applying AI/LLMs to real business problems (side projects count — we care about what you've built, not just where)
• Proficiency in Python or Typescript and comfort working with APIs (OpenAI, Anthropic, or similar LLM providers)
• Build repeatable skills or plugins for popular LLM clients to empower your team
• Educate and mentor team members to become more AI-Native
• A builder's mentality: you'd rather ship a working prototype than write a spec about one
• Ability to work cross-functionally and translate between technical and non-technical stakeholders

Preferred requirements:

• Experience with workflow orchestration tools (Agent SDK, n8n, Make, Zapier, or custom Typescript/Python pipelines)
• Prior work at a DTC subscription company or growth-stage startup
• Familiarity with prompt engineering, RAG architectures, or fine-tuning
• Experience building internal tools used by non-technical teams
• Familiarity with marketing platforms and data infrastructure — ideally some combination of Braze, Google Ads, Meta Ads Manager, Snowflake, or equivalent
• Strong enough understanding of growth marketing to ask the right questions and build tools that practitioners actually want to use

Technologies You'll Use

• LLM APIs: OpenAI, Anthropic, and/or open-source models
• CRM & Marketing: Braze, Google Ads, Meta Ads Manager
• Data: Snowflake, SQL, Tableau, dbt, Hex
• Orchestration: Typescript, Agent SDK, Vercel AI SDK, Python, n8n, Make, or similar
• Collaboration: Slack, Notion, Jira, Google Workspace

Benefits

 🩺 Health Insurance coverage (Canada Life)

⛱ Flexible Paid Time Off

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave.

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly.

🧘🏽‍♀️ Wellness perks: fitness subsidies to build a healthy lifestyle

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

At Coconut Software, we’re not just building data pipelines, we’re architecting the source of truth that powers the future of financial connections. As a Senior Analytics Engineer, you will be the glue between our technical data infrastructure and our business outcomes. While your primary focus is building a world-class modeling layer in dbt and Looker, you are equally comfortable putting on your Data Analyst hat to help stakeholders uncover the "why" behind the numbers.

Your role extends beyond technical modeling; you will be a mentor, a guide, and an advocate for data best practices. You’ll help foster an inclusive, psychologically safe environment where data professionals can do their best work. By proactively improving our data modeling standards and strengthening cross-functional collaboration, you will ensure our team delivers high-quality, actionable insights that meet both user needs and business goals.

Data @ Coconut:

• We are currently in an exciting phase of growth, migrating our entire data estate from legacy Postgres and Redshift environments to a modern Databricks Lakehouse.
• Our stack is built for scale: Databricks for storage and compute, dbt for our transformation and semantic layer, and Looker (LookML) for business intelligence.
• We don't follow rigid Scrum, but we do work in an agile, iterative way, and try to continuously improve and implement what works for us.
• We work in a blameless culture and have a continuous improvement mindset.

[Note: On Call] We strive to provide service excellence in all areas, as such, roles in our Engineering department are expected to contribute to our collaborative on-call rotation, working with your team to support our systems and ensuring application availability/reliability. Each team will have their own rotation schedule.

YOU’RE FIRED UP ABOUT:

Team Elevation

• Mentor and support data analysts, data engineers and developers, fostering a collaborative and psychologically safe environment.
• Set high standards for technical excellence in SQL, dbt modeling, and LookML architecture.

Technical Delivery & Ownership

• Collaborate with other analytics engineers on the migration of legacy logic from Redshift/Postgres into performant Databricks silver and gold layers.
• Independently implement complex data models in dbt, demonstrating expertise in modularity, testing, and performance optimization on Spark.
• Own the LookML layer, ensuring our explores and dashboards are performant, intuitive, and accurate.
• Act as a "Hybrid Analyst," comfortably balancing long-term engineering projects with ad-hoc requests to support the business. 
• Translate stakeholder questions into Looker-based reports and visualizations, ensuring the business has the right insights at the right time.

Data Architecture & System Design

• Lead technical data planning through discovery, design, and release, ensuring clear documentation for data catalogs and version tracking.
• Identify opportunities for "data debt" reduction and architectural improvements in our Lakehouse and semantic layers.
• Proactively address system characteristics like latency and throughput, ensuring our data pipelines are optimized for cost and speed.

Product and Business Partnership

• Act as a subject matter expert in your data domain, contributing to business strategy to ensure we are measuring what matters.
• Provide engineering perspectives on the product roadmap, clearly communicating data feasibility and reporting limitations.

WHAT YOU BRING TO THE TEAM:

• 5+ years of applied experience in an Analytics Engineering or Data role with a solid track record of technical leadership in B2B/SaaS environments.
• Extensive experience architecting dbt projects and managing complex Looker environments.
• Solid experience using Looker (or similar BI tools like Tableau or Power BI) to build dashboards and solve complex data requests.
• Strong architectural understanding of modern data stacks, with proven experience in Databricks.
• Expertise in writing, improving, and troubleshooting complex SQL queries.
• A passion for learning and exploring how AI/LLMs (like Google Gemini) can be integrated into the data lifecycle.
• The ability to successfully collaborate cross-functionally, gathering requirements and delivering results to different teams and departments.
• Excellent interpersonal and communication skills; you can relay complex technical ideas to anyone in the building

This posting is for a vacant position. The expected hiring range for this role is $120,000 - $160,000.

The base salary for this position is listed to support candidates to align themselves within the target range. The range is grounded in comprehensive analysis of national compensation data for similar roles and company sizes in the technology sector, alongside a review of our internal compensation framework to ensure pay equity across the company. Note that ranges may evolve over time.  We aim to provide a fair offer and hire within this specified range. The final offer for this position will take a candidate's background, experience, skills, and internal equity into consideration. Top performers’ compensation will be reviewed annually, as part of our Performance Acceleration program (Performance Reviews, Compensation Reviews, etc.).  

1-2 years, full-time (fixed term opportunity)

Location - Remote (Canada)

Though we have an office based in Calgary, this is a remote position that is open to candidates across Canada. PurposeMed's office is located on the unceded and traditional territories of the peoples of the Treaty 7 region which includes the nations of the Siksika, the Piikani, the Kainai, the Îethka Stoney Nakoda which consists of the Chiniki, Bearspaw, and Good Stoney Bands, and people of the Tsuut’ina First Nation. The city of Calgary is also homeland to the historic Northwest Métis and to the Otipemisiwak Métis government, Métis Nation Battle River Territory, Nose Hill Métis District 5 and Elbow Métis District 6.

Who we hope to find:

This 1–2 year fellowship is designed explicitly as a transition-to-industry opportunity. It bridges the gap between academic training and real-world application in digital health, clinical operations, and business analytics, while maintaining the academic rigour and publication support expected of a postdoctoral position.

The Fellow will be formally affiliated with the University of Calgary and embedded within PurposeMed’s Data and Analytics team. This dual structure offers a rare professional advantage: a named academic home combined with direct industry immersion. Most uniquely, you will be supported by a three-person supervisory triad—academic, clinical, and technical—ensuring you grow in all three dimensions simultaneously through the mentorship of Dr. Ranjani Somayaji (U of C), Dr. Caley Shukalek (CMO), and our Head of Data.

In this role, you’ll make an impact by:

Elevating Patient Care & Health Equity

• Applying biostatistical methods including regression analyses, ROC curves, risk scoring, and survival analysis to real-world healthcare datasets
• Partnering with clinical, operations, and product teams to design and conduct analyses that drive decision-making and improve patient outcomes
• Participating in patient communication initiatives that make analytical findings accessible to the communities PurposeMed serves

Bridging Data Rigor and Business Strategy

• Translating complex statistical insights into actionable recommendations for clinical, ops, and leadership teams
• Collaborating in the development, validation, and communication of metrics and KPIs for clinical, operational, and business performance
• Collaborating with PurposeMed's data engineering team to extract, manage, and transform data from cloud-based healthcare data warehouses

Advancing Academic Research & Partnerships

• Contributing to peer-reviewed publications, white papers, and conference presentations in collaboration with Dr. Somayaji
• Collaborating with government agencies, non-profits, and community partners, including HIV CTN-affiliated organizations, on joint research initiatives
• Receiving structured mentorship in business analytics, product decision-making, and applied healthcare data science

We need someone who has:

• A PhD in Biostatistics, Statistics, Epidemiology, or a closely related quantitative field (conferred or imminent, PhD candidates with a confirmed defense timeline are welcome to apply)
• Demonstrated experience with advanced statistical analyses: regression modeling (linear, logistic, mixed-effects), ROC curves, risk score development and validation, survival analysis (Kaplan-Meier, Cox proportional hazards)
• Proficiency in R, including tidyverse and statistical modeling packages
• Working knowledge of SQL for querying healthcare data warehouses
• Excellent written and verbal communication skills and is able to present findings to clinical, operational, and non-technical audiences
• A proven ability to work independently and collaboratively in multidisciplinary teams

It would also be great if you have:

• Experience using Python (pandas, scikit-learn, statsmodels)
• Familiarity with cloud data warehouses (Snowflake, BigQuery, or Redshift) and version control (Git)
• Prior experience with real-world healthcare or clinical research datasets, particularly those with missingness, selection bias, or irregular observation times
• Exposure to BI tools (Looker, Tableau, Power BI) or R dashboard frameworks (Shiny, flexdashboard)
• Awareness of dbt or similar data transformation frameworks
• An interest in or prior experience with LGBTQ+ health, HIV/sexual health, gender-affirming care, or chronic disease management
• A prior connection to the HIV CTN, Alberta Innovates, University of Calgary research networks, or Dr. Somayaji's research group

Compensation:

• $80,000 CAD a year
• Please note that this role will be hired through the University of Calgary which provides a benefits package. This role will be contracted to PurposeMed and will not be eligible for the benefits listed below.

Do you think you could be our next Postdoctoral Fellow? We look forward to seeing your application!

#LI-Remote

ABOUT US

Localcoin, founded in 2017 with headquarters in Toronto, is on a mission to simplify the process and experience of buying or selling digital currencies globally. We envision bringing digital currency to the mainstream financial market through partnerships with leading corporate and franchised retail spaces. With terminals across Canada, Poland, and the APAC region—including Australia, Hong Kong, and New Zealand—Localcoin is now the fastest-growing Bitcoin ATM operator in the world.

At its core, Localcoin believes that everyone should be able to own cryptocurrency and have a deep understanding of blockchain technology. As a member of our rapidly growing team, you'll join a talented, dynamic group of team members who will encourage you to learn, grow, and thrive in your career every step of the way.

If you're a self-starter looking to hone your skills in a startup environment that fosters innovation, transparency, and team connectivity, we look forward to hearing from you!

THE ROLE

We are seeking a Senior DevOps Engineer with deep AWS expertise, multi-account architecture experience, and strong leadership capability. This role owns our cloud infrastructure strategy, CI/CD systems, security posture, observability stack, and infrastructure governance across production and regulated environments.

This is a hands-on technical  role with a strong emphasis on execution (80%), complemented by mentoring, coaching, and knowledge transfer (20%) to other team members. The role is responsible for designing and delivering resilient systems that meet SLAs while maintaining compliance and operational excellence.

This position will be based out of our Etobicoke, ON office, with an expectation of working in-office two days per week.

WHAT YOU’LL BE DOING 

Cloud Architecture & Multi-Account Strategy

• Design and manage AWS Organizations across multiple accounts 
• Architect multi-region, highly available systems aligned with defined SLAs
• Design secure VPC/private subnet strategies, Transit Gateways, VPN/NGINX tunnels
• Implement expert-level IAM governance (least privilege, Verified Permissions, SSO)
• Continuously evolve cloud architecture to support fintech-grade reliability and compliance

Infrastructure as Code & CI/CD Leadership

• Lead advanced Terraform implementations across multi-account environments
• Design scalable module architecture and state management strategies
• Own and scale GitLab CI/CD pipelines and SaaS runners
• Build AMI pipelines and infrastructure automation using Python, Go, or Bash aiming deterministic builds
• Improve deployment velocity without compromising security

Containers, Orchestration & Observability

• Architect and operate Kubernetes (EKS) or ECS environments
• Manage ECR, image scanning, auto-scaling
• Implement observability using Datadog (preferred) or Prometheus/Thanos
• Define SLIs/SLOs aligned to business SLAs
• Lead incident response and root cause analysis
• Architect and operate RDS databases

Security & Compliance

• Resolve CIS Benchmark and Security Hub findings
• Harden AWS environments and container workloads
• Manage secrets via Vault or AWS Secrets Manager
• Support PCI or regulated fintech/crypto requirements
• Strengthen our cloud security stack across infrastructure and pipelines

Edge, Connectivity & Cloudflare

• Manage Cloudflare infrastructure (Firewall, WARP, Zero Trust, Access, DNS)
• Design secure edge networking and connectivity patterns
• Support secure connectivity for crypto infrastructure components
• Lead cloud migration efforts when required

FinOps & Governance

• Implement cost optimization and tagging strategies
• Clean up unused resources and reduce cloud waste
• Build architecture documentation and operational runbooks
• Drive infrastructure governance and platform standards

WHAT WE’RE LOOKING FOR 

• 7–10 years in IT infrastructure/cloud engineering
• 5+ years owning production AWS environments
• Deep AWS architecture expertise (multi-account, security stack, networking)
• Advanced Terraform experience in complex environments
• Strong CI/CD architecture experience (GitLab preferred)
• Strong Kubernetes (EKS) or ECS experience
• Professional scripting experience (Python, Go, or Bash)
• Experience working in PCI-compliant or regulated fintech/crypto environments
• Strong understanding of SLAs and building systems around them
• Leadership capability — able to mentor and influence engineering standards
• AWS Solutions Architect – Professional (SAP-C02)
• Additional AWS certifications (DevOps Engineer Professional)
• Hands-on Datadog experience
• Experience leading FinOps programs
• Experience with Cloudflare Zero Trust & WARP
• Experience with HashiCorp Vault
• Experience with Snowflake/dbt infrastructure

WHAT YOU’LL LOVE ABOUT US

• Competitive Salary & Benefits – We value and reward our team members.
• RRSP Group Matching Program – We invest in your financial well-being.
• Hybrid Work Environment – Enjoy flexibility while being part of a dynamic team.
• Professional Development – Opportunities for learning and growth covered by Localcoin.
• Team Culture & Events – Regular socials, team meetings, and collaborative workspaces.
• Impactful Work – Play a key role in a growing company and make a real difference.

JOIN OUR INCLUSIVE TEAM

Localcoin is committed to building an inclusive, accessible, and equitable workplace. We welcome applicants from all backgrounds and do not discriminate based on race, ancestry, place of origin, color, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity or expression, age, marital status, family status, or disability.

If you require accommodation at any stage of the recruitment process, please notify the Talent team or email careers@localcoinatm.com.

Applicants must be legally eligible to work in Canada. At this time, we are not able to provide visa sponsorship.

AI DISCLOSURE STATEMENT

We want to share that we may use artificial intelligence (AI) tools to help screen and assess applications. While technology helps us stay organized and efficient, every hiring decision at Localcoin is made by real people who care about finding the best addition to our team. These tools are used to support our process—not to replace the human judgment and connection that are core to our culture.

About the Role

We are looking for a highly skilled Senior Data Engineer to become part of our core Data & AI Engineering team. In this pivotal role, you will be responsible for designing and expanding enterprise-level data infrastructure that enables ZoomInfo's internal teams to interact with data comprehensively—extracting, exploring, analyzing, and generating insights—through various platforms using ZI's internal chat agent

The ideal candidate has a strong background in big data processing, pipeline orchestration, and data modeling, with a proven track record of delivering scalable and high-quality data solutions in fast-paced, data-centric product environments. Given the dynamic nature of emerging technologies, this role requires an individual who excels at exploration and embraces continuous learning as core responsibilities. You'll constantly research and implement innovative solutions while integrating vast, diverse data sources into our AI applications, including our industry-leading LLM-powered systems

What you’ll do:

• Design, develop, and maintain high-performance, product-centric data pipelines using Airflow, DBT, and Python.
• Architect and optimize the massive-scale data warehouse and lakehouse that serves as our single source of truth for all customer data, primarily using Snowflake.
• Lead the integration of diverse structured and unstructured data sources (e.g., web data, third-party APIs) into our data ecosystem, ensuring high-quality and reliable ingestion.
• Implement and enforce Model Context Protocol (MCP) or similar architectures to feed accurate and contextual data into our LLM-powered products for applications like Retrieval Augmented Generation (RAG) and advanced search.
• Collaborate with ML engineers, data scientists, and product managers to translate business needs into scalable data solutions that directly enhance customer value.
• Define, monitor, and enforce data quality SLAs across all pipelines and products, ensuring data accuracy and lineage are a top priority.
• Mentor and coach junior engineers, promoting best practices in code quality, data architecture, and operational excellence.
• Participate in architectural decisions and long-term strategy planning for our enterprise-wide data infrastructure, with a focus on cost, performance, and reliability.

What you bring:

• Expert-level SQL for building performant, scalable queries and transformations on massive datasets.
• Strong Python programming skills with a focus on distributed computing, data manipulation, and building robust APIs.
• Production-level experience for large-scale batch and streaming data processing.
• Hands-on experience with DBT (Data Build Tool) for advanced data modeling and transformations in a modern data stack.
• Deep knowledge of Snowflake data warehouse design, optimization, and cost modeling.
• Experience implementing Model Context Protocol (MCP) or similar architectures to feed structured and unstructured data into LLM-powered systems.
• Strong understanding of data architecture concepts, including data lakes, event-driven architectures (e.g., Kafka), ETL/ELT, and data mesh.
• Proficiency with cloud platforms (GCP and/or AWS) and infrastructure as code (e.g., Terraform).

Nice to Have

• Familiarity with LLMOps, LangChain, or RAG (Retrieval Augmented Generation) pipelines.
• Experience with building embedding models or pipelines for Named Entity Recognition (NER).
• Knowledge of data cataloging tools (e.g., OpenLIneage, etc.) and lineage tracking.
• Familiarity with other distributed systems and databases (e.g., DynamoDB, Flink).

Required Non-Technical Skills

• Excellent communication skills – ability to explain complex technical concepts to both engineering teams and non-technical stakeholders.
• Strategic & Product-Oriented Thinking – can translate business objectives and customer needs into scalable, high-impact data solutions.
• Leadership & Mentorship – experience guiding and uplifting engineering teams to achieve their full potential.
• Stakeholder Management – able to collaborate effectively across departments (Product, Engineering, Sales, Compliance).
• Agility & Adaptability – thrives in ambiguous, evolving environments and can rapidly prototype and iterate on solutions.
• Strong documentation habits and ability to evangelize best practices across the organization.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of progressive experience in data engineering, with a track record of leadership and impact.

Demonstrated experience in implementing or scaling data infrastructure for a data-centric product company.

#LI-AR2

#LI-REMOTE

About the Role

As a Senior Data Engineer, you’ll play a key role in scaling and improving how we integrate and process customer data. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. You’ll also contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution.

What You’ll Do

• Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data.
• Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
• Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs.
• Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
• Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
• Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
• Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification.

• Significant experience designing and maintaining ETLs that process large-scale datasets.
• Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
• Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
• A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
• Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
• A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
• Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
• Proven leadership in technical projects, with a willingness to mentor and help others grow.

Why Work Here

• Join a mission-driven company reducing millions of pounds of food waste in grocery stores per year.
• Work on challenging, real-world problems that have a direct impact on our customers.
• Be part of a collaborative, supportive team where your ideas are valued and acted on.
• Use cutting-edge tools and platforms to solve meaningful data challenges.

We’re looking for someone who thrives on tackling complex data problems and takes pride in building systems that work seamlessly at scale. If that sounds like you, we’d love to hear from you!

This position is not eligible for immigration sponsorship

Salary Range in Canada (CAD): $137,000 - $205,000

About the team

The Integrations Ecosystem org is the bridge between ClickHouse and the rest of the data world. We build and maintain the connections that make ClickHouse accessible to the developers, data engineers, and analysts who rely on it in production every day. Our scope spans low-level database drivers, ingestion and CDC pipelines, data framework integrations, and BI connectivity — ensuring ClickHouse feels native in whatever stack our users already have.

We maintain the official language clients (Python, JavaScript, Java, Go, Rust, C++, C#) and ODBC driver; ship first-party connectors for Kafka Connect, Apache Spark, Apache Flink, dbt, and Airbyte; and own integrations with BI platforms.

This role sits on the Language Clients team, which provides the JVM foundation that everything else in the ecosystem is built on.

What you'll do

As a Senior Software Engineer on Language Clients, you'll be a technical owner of ClickHouse's Java client and JDBC driver, the foundation that our own Connectors team and a long list of external 

frameworks rely on to talk to ClickHouse.

Your primary users are engineers: the Connectors team building ClickHouse connectors for Kafka, Flink, Spark, and others, and the broader JVM ecosystem (data ingestion tools, BI platforms, data visualizations) that consumes the driver directly. Your job is to make sure they have a fast, reliable, well-designed foundation  and to treat their feedback as the signal for where the driver goes next.

In your first year you can expect to:

• Own the Java client and JDBC driver end-to-end: roadmap, API design, performance, release engineering, and partner-facing support.
• Drive throughput and latency work across the client and ClickHouse server
• Partner day-to-day with the Connectors team as an embedded internal customer: understand what their connectors need from the driver, and ship it.
• Engage directly with external partners across data ingestion, and data visualization on interoperability, regressions, and roadmap alignment.
• Ship visible, measurable wins in throughput, stability, and developer experience.

We expect you to bring opinions, artifacts, and written proposals to shape where we invest next.

About you

• 5+ years of software engineering experience with a significant portion focused on data-intensive systems: drivers, SDKs, ingestion, CDC, streaming, or analytics.
• Deep Java and JVM expertise: memory model, GC tuning, profiling, and the ability to reason about throughput and latency at the level of bytes on the wire.
• Hands-on experience building or substantially extending a library that other engineers depend on. You understand that API design compounds, and that a breaking change in a widely used library is a very different thing from a breaking change in an application.
• Strong grasp of database fundamentals: SQL, query execution, and analytical/OLAP workloads. Judgment about when to lean on framework abstractions versus when to drop down to the protocol.
• Solid instincts on concurrency in the JVM: executors, reactive streams, backpressure, connection pooling, and the failure modes that come with each.
• Thoughtful, transparent use of modern AI development tools (Claude Code, Cursor, Copilot, or equivalents) combined with strong independent design and code review judgment. We expect engineers to lean on AI where it's genuinely helpful and to be explicit about where they didn't. Resistance to AI tooling is a mismatch for this team and so is over-reliance without the underlying engineering depth to review what comes out.
• Excellent written communication. Most of our coordination happens in design docs, PR descriptions, and RFCs.
• Genuine open-source disposition: comfort engaging with community issues, external contributors, and public design discussions. You don't need to be a maintainer of a well-known project, but you do need to be comfortable working in the open.

Nice to have

• Working knowledge of JDBC internals, ADBC, or Arrow / Arrow Flight SQL.
• Experience designing or evolving wire protocols, or contributing to a widely-used network client.
• Prior contributions to open-source data infrastructure (Kafka, Spark, Flink, dbt, Debezium, Iceberg, or similar).
• Working knowledge of ClickHouse or another columnar/OLAP engine.

Viral Nation is looking for a seasoned Principal Product Manager to own the vision, strategy, and execution of our core data and platforms. This is a highly technical and strategic role focused on building the "data-as-a-product" foundation that powers our products, services, internal operations, and advanced AI workloads.

We are seeking a leader who thinks in terms of data architecture, scalability, and quality. You will be responsible for the roadmap of our data pipelines, data warehousing solutions, and the systems that make data accessible, reliable, and "AI-ready" for all stakeholders, from business intelligence analysts to marketing specialists. Your work will be critical in developing the data infrastructure that fuels our Big Data solutions and the next generation of AI-driven products and services.

What You'll Do Here:

• Define and own the product vision, strategy, and roadmap for Viral Nation's data platform, focusing on data pipelines (ETL/ELT), data warehousing, and analytics infrastructure.
• Translate complex business needs and AI/ML requirements into clear, technical user stories and specifications for data engineering teams.
• Develop a deep functional and technical understanding of our data architecture, from ingestion and transformation to storage and consumption, to identify bottlenecks and opportunities for innovation.
• Partner directly with the AI Science team to define requirements and build scalable data solutions for tuning, evaluating, and deploying AI models.
• Act as a key technical partner to data engineers and analysts, using your strong SQL skills to perform data analysis, validate data models, and ensure data quality.
• Work in close partnership with data engineering, architecture, engineering, application, and AI teams to ensure our data platform meets their needs for reliability, scalability, and performance.
• Define and monitor key performance indicators (KPIs) for the data platform, such as data freshness, pipeline uptime, and query performance, to drive continuous improvement.
• Research, evaluate, and recommend new data technologies, tools, and partners (e.g., in the data warehousing, transformation, or observability space) to enhance our platform capabilities.
• Work closely with the Product, Engineering, DevOps and AI teams to align the data platform roadmap with overarching technology goals.
• Be comfortable in a highly dynamic, agile environment
• Stay current with emerging technologies and trends in data engineering, data warehousing, and AI systems.

What You'll Need To Have:

• Bachelor’s degree in Computer Science, Data Science, Engineering, Business Analytics, or a related field — or equivalent experience demonstrating technical excellence and business fluency.
• 7+ years’ experience in technical product management, with at least 3-5 years specifically focused on data platforms, data warehousing, or data infrastructure.
• Strong SQL skills are essential. You must be comfortable writing complex queries, analyzing data, and validating data models independently.
• Deep technical knowledge of modern data ecosystems, including data pipeline (ETL/ELT) orchestration (e.g., Airflow, dbt) and data warehousing concepts and architecture.
• Direct experience with Snowflake (data warehousing, streams, tasks) is a major plus.
• Strong knowledge of the concepts, tools, practices and techniques of product management and working in an agile environment.
• Strong experience with agile project management and tools (Jira is required), particularly in managing technical backlogs for data engineering teams.
• Experience with cloud data services, especially GCP, is a strong asset.
• Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Knowledge of Machine Learning concepts is a strong asset.

The Role

The Data Practice Director is a senior leadership role within Caylent's Cloud Data Engineering (CDE) practice, reporting directly to the Data Practice Leader. This person is responsible for operationalizing the practice strategy, leading a team of data professionals, and owning delivery excellence across a portfolio of client engagements. They are the connective tissue between strategic direction and day-to-day execution, ensuring the practice delivers consistent, high-quality outcomes while scaling to meet growth targets.

Your Assignment

Practice Operations and Delivery

• Own end-to-end delivery oversight for a portfolio of data engineering and analytics engagements, ensuring on-time, on-budget, and high-quality outcomes.
• Drive operational rigor across the practice including utilization management, staffing coordination, margin tracking, and engagement health reviews.
• Develop and enforce delivery standards, reusable frameworks, and best practices that enable consistent, scalable execution across the team.
• Serve as an escalation point for active engagements, helping resolve technical blockers, scope issues, and client concerns in partnership with delivery leads.
• Partner with the Practice Leader to translate the strategic roadmap into executable quarterly priorities and team-level OKRs.

Team Leadership and Development

• Directly lead and develop a team of data engineers, architects, and analytics professionals across the practice.
• Set clear performance expectations, conduct regular reviews, and provide ongoing coaching to build a high-performing, engaged team.
• Partner with recruiting and workforce planning to identify talent gaps, support hiring decisions, and onboard new team members effectively.
• Foster a culture of ownership, continuous learning, and technical excellence across a globally distributed team.
• Identify and develop emerging leaders within the practice, creating growth pathways aligned to practice needs.

Client Engagement

• Build trusted advisor relationships with key client stakeholders, acting as a senior point of contact for delivery and strategic guidance.
• Partner with the sales and GTM teams to support business development activities including scoping, proposal development, and technical solutioning for new and existing accounts.
• Identify and pursue expansion opportunities within active client engagements, surfacing new use cases and service offerings that align with client needs.
• Represent Caylent with credibility and professionalism in client-facing conversations at the director and VP level.

Practice Growth and Enablement

• Collaborate with the Practice Leader on go-to-market positioning, service offering development, and internal capability building.
• Contribute to thought leadership content including whitepapers, webinars, and conference presentations that elevate the practice's external profile.
• Stay current on trends in the modern data ecosystem and work with the team to incorporate relevant innovations into our delivery approach.
• Support the development of practice IP including accelerators, reference architectures, and reusable solution components.

Your Qualifications

Experience

• 12+ years of experience in professional services or consulting, with a strong focus on data engineering, analytics, or data platform delivery.
• Demonstrated success managing and growing a team of 20 or more data professionals in a services or consulting environment.
• Proven track record of delivering complex data projects on AWS, including data lake, lakehouse, streaming, and analytics workloads.
• Experience managing a portfolio of concurrent client engagements, balancing delivery quality with financial performance.
• Hands-on background in data architecture or engineering, with the ability to engage credibly with technical teams and client stakeholders alike.

Leadership

• Strong people management skills with demonstrated ability to develop talent, drive performance, and build team culture across geographies.
• Ability to operate effectively at multiple levels, from strategic planning conversations with the Practice Leader to hands-on engagement support with delivery teams.
• Comfortable navigating ambiguity and complexity in a fast-paced, high-growth consulting environment.
• Experience influencing senior client stakeholders (director, VP and C-level) in delivery and advisory contexts.

Technical Acumen

• Deep familiarity with the AWS data ecosystem including services such as Redshift, Glue, EMR, Kinesis, Lake Formation, and Athena.
• Working knowledge of adjacent platforms including Databricks and Snowflake, and their integration with AWS-native architectures.
• Broad understanding of data engineering fundamentals: ingestion patterns, transformation frameworks (e.g., Spark, dbt), data modeling, governance, and quality management.
• Familiarity with MLOps and data science workflows sufficient to support and position those capabilities in client conversations.

Education

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Master's degree or MBA is a plus.

Certifications

• AWS Certified Data Analytics, AWS Certified Solutions Architect, or equivalent certifications are a plus.

Preferred Qualifications

• Execution-Oriented: Skilled at translating strategy into structured plans and holding teams accountable to outcomes.
• Client-First Mindset: Genuinely invested in client success and capable of building durable, trust-based relationships.
• Collaborative Partner: Works effectively across sales, delivery, and practice leadership functions without siloed thinking.
• Clear Communicator: Able to convey complex technical and business concepts to diverse audiences with clarity and confidence.
• Growth Driver: Passionate about building teams, capabilities, and client relationships that compound over time.

Benefits

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Base Salary Range: The expected base salary range for this position is CAD $207,000 - $272,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

Are you a data engineer who loves writing code, or a full-stack developer with a knack for data? Either way, we'd love to talk. We're looking for an Intermediate Data Engineer to join us at Thinkific

As an Intermediate Data Engineer on our Data team, you'll be closely collaborating with engineering teams, designers, and stakeholders across the company to solve data problems that span the full stack — from pipelines and infrastructure to customer-facing data products. You'll be part of a small, dynamic team — the problems you'll work on won't always come with a neat brief, and we need someone who takes ownership and runs with it. Reporting to a Principal Data Engineer, your work will directly impact both internal decision-making and customer success.

Your goal will be to help shape our data products and infrastructure to have a top-line impact on our company goals. Here's how you'll accomplish this:

• Take ownership of undefined problems — dig in, scope the work, and ship solutions, whether that's a pipeline, a dashboard, a tracking implementation, or something we haven't thought of yet
• Ship customer-facing analytics dashboards and features — this is production code, not just SQL and charts
• Work directly with engineering teams to implement tracking services across our products
• Interface with teams across the company who need data solutions, translating fuzzy requirements into concrete deliverables
• Raise the bar on technical quality across the data team — through architecture decisions, reducing tech debt, code reviews, and bringing software development best practices to a high-performing data team
• Work with your team to conduct new technology research; bring fresh ideas and concepts to bear on how we integrate AI into our data workflows

The person we have in mind likely:

• Has 3–5 years of experience working across data engineering, full-stack development, analytics, or some combination — we care more about range than a specific title
• Has solid data engineering experience — you've built and maintained pipelines, worked with warehouses, and understand data modeling and quality
• Has full-stack development experience — you've shipped production code that users interact with, not just internal tooling
• Has hands-on experience with dbt and BigQuery or similar stacks (Snowflake, Databricks, etc.)
• Is self-motivated and resourceful — you ship things, communicate clearly across technical and non-technical teams, and are always looking to level up
• Is comfortable working across the stack and across disciplines; you don't need to be an expert everywhere, but you're not afraid to jump in
• For reference, our current stack is primarily dbt (SQL) with Python for data work, Looker for our Analytics layer, and React, TypeScript (with some Ruby), and embedded Looker on the product side — but we're more interested in your engineering fundamentals than specific language experience.
• Loves to learn and grow, They’ve found (and keep looking for) ways to level up their skills in this field, whether that’s through formal education, gaining professional experience, or maybe even building their own business 

These things would also be nice, but we think you could learn them on the job:

• Experience with LLM/agent development — building AI-powered data products, automated workflows, or integrating LLMs into data pipelines and analytics
• Experience with GCP and Terraform
• Any exposure to ML
• Experience white-labeling a BI tool or embedding analytics into a customer-facing product
• Experience building or maintaining event tracking systems
• Familiarity with modern data stack tools beyond dbt/BigQuery (Airflow, Dagster, etc.)
• Experience working in startup-style environments or autonomous teams within larger orgs
• Experience working in a SaaS environment

We’re committed to fair and transparent pay that reflects both where you are and where you can grow to. This role has a salary range base of $88,200 - $110,200 - $132,200 designed to capture the full journey from developing skills to excelling in the position. Most new hires start between the minimum and midpoint, which aligns with being fully capable in the role. Salaries above the midpoint are typically reserved for team members who have demonstrated strong, consistent performance, deep expertise, and a significant positive impact within the role.

For high-demand or hard-to-fill positions like this one, we may hire above midpoint for candidates who bring exceptional experience, skills, or impact potential.

Diversity, Equity, Inclusion and Belonging & Accessibility

This is just our initial idea of who we’re looking for! At Thinkific, we know that people have unique career journeys. If your experience is close to what we’ve described but you feel that you might be missing a few of the requirements, please still apply! We believe in equal opportunity and are committed to diversity, equity, inclusion, and belonging across every facet of our business.

We’re also committed to providing a comfortable and accessible interview experience for every candidate. If there are any accommodations our team can make throughout our hiring process (big or small), please let us know. 

About the Role

As the Data Engineering Manager on the Core Data Engineering team, you'll lead the team responsible for integrating customers onto Afresh's platform and continuously improving the processes and code that make those integrations faster and more reliable. Your team will also build core dataflows that power new Afresh products as they launch.

This means owning the full lifecycle of customer data integrations: from raw data ingestion through transformation and delivery to downstream product and ML teams, across both new and existing grocery customers. Afresh's customer base is growing fast! We want to integrate customers across all of our products quickly and reliably. You'll drive integration execution, integration velocity, improve data quality and pipeline reliability, and build tooling and processes that make this process seamless.

This is a hands-on management role. You'll be deeply involved in technical decisions while also coaching your team, managing execution across multiple customer projects, and collaborating closely with Solutions Engineering, Product, and other engineering teams.

What You'll Do

• Lead and grow a team of data engineers, providing mentorship, technical guidance, and career development support.
• Own execution of customer integrations across multiple product lines (Store Ordering, RecsAPI, DC, Production Planning, and more), ensuring integrations are delivered on time and at a high quality bar.
• Build core dataflows that power new Afresh products, working closely with Product and ML teams to understand requirements and deliver reliable data foundations.
• Drive integration velocity: improve the speed and predictability of getting new customers from raw data landing to production-ready, leveraging AI tooling, standardized architecture, and strong contractor enablement.
• Continuously improve integration processes and shared code: identify patterns across customer integrations and invest in abstractions, templates, and automation that reduce per-customer effort over time.
• Collaborate deeply with Solutions Engineers, Product Managers, and customer-facing teams to scope integration work, unblock dependencies, communicate progress, and ensure integrations meet our customers’ needs.
• Improve data quality and pipeline reliability by investing in better alerting, self-healing patterns, and resilience to messy or incomplete customer data.
• Champion AI-forward engineering practices: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive tasks, and push the team to the bleeding edge of modern data engineering.
• Contribute technically: reviewing code and architecture decisions, pairing with engineers on complex problems, and staying close to the work.

What Makes You a Great Fit

We encourage all highly-qualified candidates to apply, even if they don't meet every listed qualification.

• 3+ years of engineering management experience
• Strong technical background in data engineering: experience with Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar).
• Track record of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable.
• Experience managing execution across multiple concurrent projects with different customers or stakeholders, balancing competing priorities with clear communication.
• Demonstrated ability to improve team velocity through better tooling, process improvements, or automation.
• Genuine enthusiasm for AI-augmented engineering workflows. You've experimented with AI coding tools, agentic workflows, or similar, and have a vision for how they can transform data engineering and uplevel the team.
• Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering.
• Strong collaboration skills: you're effective working across engineering, product, and customer-facing teams in a fast-paced environment.

Nice to Have

• Experience in grocery, retail, or supply chain data domains.
• Prior experience at a high-growth startup navigating rapid customer expansion.

Our Tech Stack

• Python, PySpark, dbt
• Databricks (Delta Lake, Unity Catalog)
• Astronomer (Airflow) for orchestration
• Claude, GitHub, Shortcut, Notion for development workflows

Why Work Here

• We are a mission-driven company that reduces millions of pounds of food waste (and growing!) in grocery stores every year.
• Work on challenging, real-world data problems that have a direct and visible impact on customers.
• Be part of an engineering culture that's genuinely AI-forward. We want to be on the bleeding edge.
• Lead a team at a pivotal inflection point: rapid customer growth means your work directly shapes how Afresh scales.
• Collaborative, supportive environment & awesome people :)

This position is not eligible for company sponsorship.

Salary Range in Canada (CAD): $157,433 - $232,996

We are seeking a skilled Mid-Level Data Engineer to join our Data Platform team. At this level, you will be a hands-on executor and domain owner — responsible for building, maintaining, and improving the pipelines and data models that power analytics and business intelligence across the company. You will own specific areas of our BigQuery data warehouse end-to-end, delivering reliable data products within a framework set by senior and staff engineers.

This is not an architecture or strategy role — it is a role for someone who takes well-defined problems and executes them with high craft and reliability. You will work closely with data analysts, analytics engineers, and product teams, and are expected to grow toward greater technical ownership over time.

Key Duties

• • • Build and maintain production-grade ELT pipelines that ingest data from internal applications, third-party SaaS tools, and event streams into our BigQuery data warehouse.
    • Own specific data domains end-to-end — from raw ingestion through to marts — ensuring your areas of the warehouse are accurate, tested, and well-documented.
    • Write and maintain dbt models, tests, macros, and documentation within our established dbt project conventions and code review process.
    • Develop and manage Airflow DAGs on Cloud Composer or other similar tools to orchestrate data workflows, following patterns and standards set by the team.
    • Implement data quality checks and monitoring to catch anomalies before they reach downstream consumers.
    • Optimize BigQuery queries and models for cost and performance within your domain, escalating architectural tradeoffs to senior engineers when appropriate.
    • Collaborate with analysts and stakeholders to translate business data needs into well-scoped pipeline and modeling tasks.
    • Participate in on-call rotations, respond to pipeline incidents, and write clear postmortems.
    • Contribute to team documentation and runbooks so that your work is maintainable by others.
      
      Skills and experience

      Required:

      • 3–5 years of experience in data engineering or a closely related data infrastructure role.
      • Proven experience designing and implementing scalable data pipelines and warehouse architectures.
      • Strong expertise in Google Cloud Platform (BigQuery, Cloud Storage, Cloud Composer, Pub/Sub, Dataflow).
      • Hands-on experience with dbt (data build tool) — models, tests, macros, sources, and documentation — at production scale.
      • Experience building and maintaining data pipelines with Apache Airflow or a comparable workflow orchestration tool.
      • Strong proficiency in SQL, including advanced BigQuery SQL (window functions, partitioning, clustering, query optimization).
      • Proficiency in Python for data engineering tasks, including API integrations, data processing scripts, and custom operators.
      • Familiarity with data modeling concepts: star schema, dimensional modeling, slowly changing dimensions (SCD).
      • Experience with version control (Git) and collaborative development workflows (pull requests, code review).
      • Understanding of data quality, lineage, and observability best practices.
      • Startup or growth-stage mindset — comfortable with ambiguity, rapid iteration, and evolving priorities.
      • Excellent communication skills, with the ability to collaborate effectively across technical and non-technical teams

      Preferred:

      • Experience with Terraform or similar infrastructure-as-code tools for managing cloud data infrastructure.
      • Familiarity with streaming technologies such as GCP Pub/Sub, Dataflow, or Apache Kafka.
      • Knowledge of Looker, Tableau, or other BI tools and how data models power them.
      • Google Cloud Professional Data Engineer certification
        
        Why join us: 
        
        
      • Work on a modern, best-in-class GCP and BigQuery data stack with a high-performing team.
      • Influence data platform architecture decisions and grow into a senior or staff engineering role.
      • Competitive compensation, equity, and benefits with a culture that values engineering craft and continuous learning

As well as being a part of something exciting everyday, you will also receive the following benefits:

• Annual salary + bonus
• A remote first culture!
• Flex PTO 
• Health, Dental and Vision Insurance
• 13 Paid Holidays
• Company volunteer days

What we do!

NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours without even realizing it. We’re the platform that powers success for innovative tech created by SMBs, entrepreneurs and fintech startups. We’re creative problem solvers who help visionaries smash through boundaries and think beyond what’s possible so they can think about what’s next. But we’re not just built for the tech savvy. We democratize the latest payments technology so that everyone can realize the benefits of easy payments across the full spectrum of commerce. We’re all about enabling more payments in more ways and more places.

We believe that having a diverse group of employees strengthens both our work and our workplace. We’re focused on making NMI more diverse and welcoming with initiatives like having a dedicated Diversity, Equity & Inclusion action group, diversity goals for hiring, anonymized resume screening, affinity groups such as our Women's network and LGBTQ+ Network, open forums for discussions on diversity and social justice, and measuring inclusion and belonging as part of our regular employee engagement surveys.

Equal Opportunity

NMI is committed to providing equal employment opportunity for all persons regardless of race, color, religion, sex, age, marital status, national origin, sexual orientation or sexual identity, genetic information, citizen status (except those that do not have the legal right to be employed in the United States), disability, military service, service member, veteran status, or any other basis protected by applicable law.

Please be aware that all offers of employment are made subject to receipt of satisfactory background and financial checks.

Attention job applicants: Please note that in compliance with the data protection regulations within your jurisdiction, any personal information submitted with your job application may be collected and used by NMI for the purpose of recruitment and employment-related activities. By submitting your application, you acknowledge and provide explicit consent to the processing of your personal information as described in our privacy policy found on our website. For more information on how we process your information, please read our privacy policy here: https://www.nmi.com/legal/privacy-policy/

#LI-Remote

We're hiring a Senior Software Engineer to join our Infrastructure team and build the backend services and APIs that make Lithic's data accessible across the organization. You'll spend roughly 80% of your time designing and building production backend services — REST APIs that serve data from Snowflake and other sources to internal teams and systems — and 20% supporting our data platform (pipelines, dbt, Airflow). You'll partner closely with the Analytics Engineering team to expose well-modeled data through clean, reliable APIs.

Job responsibilities:

Software Engineering (~80%)

• Design, build, and maintain backend services and REST APIs that serve data from various SQL subsystems and other data sources
• Develop well-tested, production-grade Python services with clean API contracts, proper authentication, versioning, and error handling
• Work closely with the Analytics Engineering team to expose modeled data (billing, settlement, finance) through APIs that downstream consumers can rely on
• Build internal tooling and services that enable the broader organization to self-serve their data needs without writing SQL
• Participate in code reviews, system design discussions, and engineering best practices across the Infrastructure org
• Contribute to service observability: logging, metrics, alerting, and on-call practices for the services you own

Data Engineering (~20%)

• Maintain and improve existing data pipelines that move data from source systems into Snowflake (Airflow, Airbyte)
• Contribute to the dbt project alongside the Analytics Engineering team — model improvements, test coverage, and data quality
• Support data governance practices including access controls, lineage documentation, and data quality standards

Qualifications:

Required:

• Strong Python proficiency with experience building backend services and REST APIs
• Experience with web frameworks such as FastAPI, Flask, Django, or similar
• Solid SQL skills and hands-on experience with modern cloud data warehouses (Snowflake strongly preferred)
• Experience designing and building production APIs with proper authentication, versioning, and error handling
• Familiarity with CI/CD, automated testing, and operational reliability practices
• A track record of shipping reliable, well-tested services in production environments
• Comfort navigating ambiguity and driving projects forward with minimal oversight

Preferred:

• Experience with data pipeline development using tools like Airflow, Airbyte, Dagster, or similar
• Familiarity with dbt or similar transformation frameworks
• Experience in fintech, payments, or other financial services environments
• Familiarity with AWS services (Lambda, S3, RDS, API Gateway, ECS/Fargate)
• Kafka or event streaming experience
• Infrastructure-as-code experience (Terraform, Pulumi)
• Experience at a company processing high transaction volumes where correctness and reliability are non-negotiable

The annual Canadian salary range for this role is CA$170,000 - CA$280,000 plus equity. This salary range is inclusive of several career levels at Lithic and will be narrowed during the interview process based on the candidate's experience and qualifications.

This is a remote position. However, candidates must be located in the United States, Canada, Netherlands, Poland, or Czech Republic. We do not offer visa sponsorship or assistance.

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The role

Benefits

🩺 Health Insurance coverage (Canada Life)

⛱ Flexible Paid Time Off

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave.

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly.

🧘🏽‍♀️ Wellness perks: fitness subsidies to build a healthy lifestyle

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

As a senior technology leader, you will help build our technology platform to enable 10 million change-makers to deliver a billion acts of goodness by 2025. We seek a platform-first Architect to lead enterprise patterns for reliable, governed, AI-driven, and cost-effective solutions at scale across our technology portfolio. You will design how data flows across the company, from ingestion to consumption, while ensuring our AI systems are secure, auditable, and maintainable. This role requires practical systems thinking and the ability to influence senior engineers and leadership toward consistent, enterprise-wide architecture outcomes that align our data and AI strategy with broader business goals.

If you're passionate about leveraging modern technology, data and AI for positive impact and eager to contribute to a mission-driven organization, we want to hear from you.

What you will do:

• Develop and maintain end-to-end tracks with our data and AI focus technology strategy and architectural portfolio
• Mentor engineers and technical leadership by providing clear patterns, ensuring adherence to architectural patterns, and offering hands-on guidance for complex implementations
• Lead architecture decisioning through Architecture Decision Records (ADRs), standards, and design reviews
• Oversee architectural reviews, code reviews, and system performance analysis to ensure quality standards and sustainable delivery momentum
• Foster a culture of collaboration, knowledge sharing, and continuous learning through mentorship, team collaboration, and workshops
• Enable governed data consumption through clear data contracts, curated datasets, and consistent serving patterns including domain marts
• Standardize end-to-end data flow patterns including ingestion, transformation, storage, serving, and retirement with repeatable templates
• Set platform standards for orchestration and reliability including SLAs, retries, idempotency, backfills, runbooks, and operational dashboards
• Establish enterprise data quality practices including critical data elements, quality rules, validation layers, monitoring, and issue triage workflows
• Drive governance-by-design by embedding metadata, lineage, classification, and ownership into platform patterns
• Drive adoption of AI governance architecture for agentic solutions including controls for data privacy and model lifecycle
• Define AIOps standards ensuring AI systems have traceability, quality measurement, incident response readiness, and cost guardrails
• Collaborate with stakeholders and product management to identify, prioritize, and mitigate technical risks and challenges
• Stay informed about industry regulations, security standards, and compliance requirements to ensure solutions meet necessary standards

What you’ll bring:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• 7+ years in software development methodologies, architecture, and implementation of large scale enterprise systems
• 4+ years focused on data engineering, data management, or data platform architecture and designing AI solutions including AIOps practices
• Structured problem solving to turn ambiguous requirements into scalable, low-cost solution patterns
• Ability to think strategically while paying close attention to technical details
• Proven experience building or evolving an enterprise data platform including standards and adoption across multiple teams
• Demonstrated ability to design governance-ready AI solutions including evaluation strategies, privacy safeguards, and auditability
• Strong expertise in system architecture, cloud computing, distributed systems, and integration technologies
• High bar for operational readiness, actionable documentation, and treating governance as a built-in platform feature
• Deep experience across modern data platform capabilities including AWS Glue, Step Functions, Airflow, dbt, Spark, and Snowflake
• Proficiency in programming and analytics using Python, SQL, and Jupyter Notebooks
• Experience with agentic frameworks such as LangChain, LlamaIndex, or LangGraph and AIOps tooling like LangFuse
• Familiarity with Agile development methodologies and the ability to adapt to a fast-paced environment
• Strong understanding of security principles, performance optimization, scalability, and reliability
• Demonstrated influence towards simplicity and repeatability in architecture

Nice to Have:

• Experience operating in regulated environments, (SOC2, ISO 27001, or GDPR).
• Familiarity with federated domain ownership models, where domains ship data products while the platform provides shared standards and tooling.
• Experience designing and scaling platform observability for data pipelines, streaming systems, and AI services.
• Familiarity with medallion architecture patterns
• Experience in modern data platform capabilities, including:
• Streaming: Apache Kafka, AWS MSK, AWS Kinesis, GCP Pub/Sub
• Metadata and governance: DataHub, Atlan or similar

As a senior technology leader, you will help build our technology platform to enable 10 million change-makers to deliver a billion acts of goodness by 2025. We seek a platform-first Architect to lead enterprise patterns for reliable, governed, AI-driven, and cost-effective solutions at scale across our technology portfolio. You will design how data flows across the company, from ingestion to consumption, while ensuring our AI systems are secure, auditable, and maintainable. This role requires practical systems thinking and the ability to influence senior engineers and leadership toward consistent, enterprise-wide architecture outcomes that align our data and AI strategy with broader business goals.

If you're passionate about leveraging modern technology, data and AI for positive impact and eager to contribute to a mission-driven organization, we want to hear from you.

What you will do:

• Develop and maintain end-to-end tracks with our data and AI focus technology strategy and architectural portfolio
• Mentor engineers and technical leadership by providing clear patterns, ensuring adherence to architectural patterns, and offering hands-on guidance for complex implementations
• Lead architecture decisioning through Architecture Decision Records (ADRs), standards, and design reviews
• Oversee architectural reviews, code reviews, and system performance analysis to ensure quality standards and sustainable delivery momentum
• Foster a culture of collaboration, knowledge sharing, and continuous learning through mentorship, team collaboration, and workshops
• Enable governed data consumption through clear data contracts, curated datasets, and consistent serving patterns including domain marts
• Standardize end-to-end data flow patterns including ingestion, transformation, storage, serving, and retirement with repeatable templates
• Set platform standards for orchestration and reliability including SLAs, retries, idempotency, backfills, runbooks, and operational dashboards
• Establish enterprise data quality practices including critical data elements, quality rules, validation layers, monitoring, and issue triage workflows
• Drive governance-by-design by embedding metadata, lineage, classification, and ownership into platform patterns
• Drive adoption of AI governance architecture for agentic solutions including controls for data privacy and model lifecycle
• Define AIOps standards ensuring AI systems have traceability, quality measurement, incident response readiness, and cost guardrails
• Collaborate with stakeholders and product management to identify, prioritize, and mitigate technical risks and challenges
• Stay informed about industry regulations, security standards, and compliance requirements to ensure solutions meet necessary standards

What you’ll bring:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• 7+ years in software development methodologies, architecture, and implementation of large scale enterprise systems
• 4+ years focused on data engineering, data management, or data platform architecture and designing AI solutions including AIOps practices
• Structured problem solving to turn ambiguous requirements into scalable, low-cost solution patterns
• Ability to think strategically while paying close attention to technical details
• Proven experience building or evolving an enterprise data platform including standards and adoption across multiple teams
• Demonstrated ability to design governance-ready AI solutions including evaluation strategies, privacy safeguards, and auditability
• Strong expertise in system architecture, cloud computing, distributed systems, and integration technologies
• High bar for operational readiness, actionable documentation, and treating governance as a built-in platform feature
• Deep experience across modern data platform capabilities including AWS Glue, Step Functions, Airflow, dbt, Spark, and Snowflake
• Proficiency in programming and analytics using Python, SQL, and Jupyter Notebooks
• Experience with agentic frameworks such as LangChain, LlamaIndex, or LangGraph and AIOps tooling like LangFuse
• Familiarity with Agile development methodologies and the ability to adapt to a fast-paced environment
• Strong understanding of security principles, performance optimization, scalability, and reliability
• Demonstrated influence towards simplicity and repeatability in architecture

Nice to Have:

• Experience operating in regulated environments, (SOC2, ISO 27001, or GDPR).
• Familiarity with federated domain ownership models, where domains ship data products while the platform provides shared standards and tooling.
• Experience designing and scaling platform observability for data pipelines, streaming systems, and AI services.
• Familiarity with medallion architecture patterns
• Experience in modern data platform capabilities, including:
• Streaming: Apache Kafka, AWS MSK, AWS Kinesis, GCP Pub/Sub
• Metadata and governance: DataHub, Atlan or similar

Overview

The Ads DSE team builds the core capabilities that power Instacart's off-platform advertising, secure data collaboration (cleanrooms), automated taxonomy management, and their associated platform foundations. We are hiring a Senior Engineer II (L6) to co-own the technical roadmap, modernize our data solutions infrastructure, scale off-platform integrations and measurement capabilities, extend our cleanroom collaboration capabilities, and automate taxonomy change management workflows. This role is pivotal for cross-team collaboration, developer productivity, and AI-driven development initiatives.

You are a senior technical leader who designs and ships scalable, data‑intensive systems; drives cross‑team execution; and raises engineering standards. You’ll partner closely with Product, Data Science, Data Platform, and Governance teams to build reusable abstractions and deliver high‑impact features across our pillars: Off‑platform, Data collaboration (cleanrooms), Ads Taxonomy, Platform, and New Initiatives (AI). You will mentor L4/L5 engineers, act as an IC tech lead (no direct reports), and help define a future on‑call model and SLOs.

About the Job

• Technical leadership and roadmap
• Lead architecture for reusable, scalable systems across off‑platform workflows, cleanrooms, taxonomy automation, and the Ads Data Solutions Platform.
• Evolve core abstractions, testing, CI/CD, observability, and cost efficiency; proactively drive modernization.
• Propose and drive initiatives on behalf of engineering management; align stakeholders and manage dependencies.

• Pillar execution
• Off‑platform: expand and harden integrations with external advertising platforms; design privacy-forward activation and identity workflows; reduce reliance on third-party intermediaries; and build measurement ingestion pipelines for performance signals such as reach, frequency, and conversions.
• Data collaboration (cleanrooms): extend our cleanroom orchestration and governance tooling (multi-cleanroom support, policy enforcement), develop reusable query templates and partner configurations, optimize pipelines for cost and performance, and scale secure data collaboration deployment and management.
• Ads Taxonomy: lead intake automation (UI + backend) and release workflow improvements to reduce manual effort and cycle time.
• Platform: assist with platform modernization and developer tooling improvements; contribute to an on‑call/SLO strategy as we mature operations.
• AI‑first engineering
• Use AI‑assisted tools daily for design, coding, tests, and docs; define team prompt patterns and workflows; identify AI opportunities in internal tools and ops.
• Product quality, privacy, and security
• Translate ambiguous requirements into pragmatic phases (POC, pilot, production) with clear SLAs/SLOs.
• Champion security‑by‑design, data governance, and privacy compliance (e.g., GDPR/CCPA) across pipelines.

• Mentorship and collaboration
• Mentor engineers up to L5; set code quality and review standards.
• Build cross‑team partnerships (Ads Manager, Measurement Science, Data Platform, Privacy/Legal, and external platforms).

About You

Minimum Qualifications

• Proven senior‑level impact
• 8+ years of software engineering experience (typically 10+ for this level) delivering and operating large‑scale backend/data systems; led cross‑team projects and architectural decisions.
• Backend and data engineering
• Strong in Python and one of Ruby or Go; services/APIs (REST/gRPC); integrations with third‑party APIs (e.g., Meta, Google, The Trade Desk).
• Data pipelines with DBT and Airflow; Spark/Databricks; advanced SQL and performance tuning.
• Snowflake and AWS experience; cost‑aware design; workflow orchestration (e.g., Temporal) and event‑driven patterns.
• Ads/cleanrooms/privacy
• Experience with ad‑tech/programmatic and measurement integrations; cleanrooms (Snowflake DCR, shares/listings); identity/matching (UID2, RampID) and deconfliction.
• Working knowledge of privacy and compliance practices (GDPR/CCPA) in data workflows.
• Platform excellence
• CI/CD, containers, test strategy; observability (metrics/logs/tracing) with tools like Datadog; incident readiness and SLO thinking.
• AI fluency (must‑have)
• Demonstrated, recent hands-on use of AI‑assisted development tools (e.g., GitHub Copilot, Cursor, OpenAI‑based assistants) to improve speed and quality.
• Experience defining reusable prompts/workflows for team use and contributing to AI‑enabled internal tools or automation.
• Ability to evaluate when to apply AI vs. deterministic systems; familiarity with evaluation, guardrails, and security/privacy implications in AI usage.
• Collaboration and communication
• Clear technical writing; stakeholder management; ability to drive consensus and unblock execution.

Preferred Qualifications

• Direct experience with UID2/TTD integrations, Roku/Pubmatic/NBCU, or Meta Advanced Analytics/Google ADH pipelines.
• Catalog/taxonomy, entity lineage, or custom hierarchy systems.
• Snowflake governance patterns, partner data collaboration at scale.
• Vendor/partner management and external API certification programs.
• Building AI‑powered internal tools (e.g., Slackbots, data assistants).

Why this role is a great opportunity....

• Lead foundational, high‑visibility initiatives and translate them into measurable impact on revenue, efficiency, and partner adoption.
• Co‑own the technical roadmap with scope to define abstractions, standards, and AI‑first workflows across multiple pillars.
• Ship impactful features end‑to‑end: direct UID2 activation, Share Manager extensions, taxonomy intake automation, and platform modernization.
• Collaborate with strong cross‑functional partners and enjoy occasional trips to our Toronto office to connect with the broader engineering community.
• Help define our future on‑call model and operational excellence standards as we scale.

Overview

Are you ready to take your development skills to the next level? We’re looking for a Senior Software Engineer to join our Ads team. You’ll play a critical role in the evolution of our Ads suite and help build world-class reporting solutions across various platforms, ensuring that advertisers and retailers receive timely, accurate, and actionable data insights. By working closely with Product Designers, Product Managers, Data Scientists, Machine Learning Engineers, and other cross-functional partners, you’ll contribute to the advancement of our Ads suite and guarantee a seamless flow of data to our users.

The Instacart Ads team is at the forefront of refining our Ads products and supporting infrastructure, so your work will directly enhance our capability to process petabyte-scale data and deliver reports essential for billing, strategic decision-making, and partner management.

Our products are used by millions of people every year. To meet–and exceed–expectations we are rapidly improving and modernizing our ads platform, helping raise the quality bar for our products across the entire organization. Sound exciting? Keep reading.

The Ads team is a diverse group of spirited and highly-dedicated engineers focused on crafting and delivering comprehensive reporting solutions to our advertisers and retailers.

Our team thrives on dynamic challenges, and we take pride in developing and maintaining scalable and fault-tolerant metrics delivery systems. We've embraced a culture of open and candid collaboration where everyone's views matter, allowing us to continuously innovate and make substantial impact to the digital advertising industry through our work.

Our tech stack includes but is not limited to Rails, Go, DBT, Airflow, Scala, Apache Spark, Databricks, Delta Lake, Snowflake, Python and Terraform. We believe in constantly learning, growing and adopting the most efficient practices that enable us to deliver quality data services to our stakeholders. If you're a detective at heart, love solving complex problems, and are passionate about the intersection of data and technology, you'll fit right in!

Overview of the Ads teams that are currently hiring: 

• Ads Measurement & Data: Our cutting-edge data team is responsible for building scalable, reliable, and maintainable ETLs and its underlying architecture and platform. We directly support critical internal and external systems and metrics such as billing, attribution, spam detection, etc. Our non-functional requirements are achieved through streaming and batch processing using Scala-Spark, Airflow, DBT, Python, and Go. If you're interested in working cross-functionally with several key stakeholders, helping shape our data strategy, building distributed systems, and solving complex data architecture challenges in a fast-paced, high-impact environment, this could be the opportunity for you!

• Advertiser Optimization: We power Instacart’s advertising business by creating innovative solutions that maximize ad performance and deliver measurable value to our partners. Through advanced algorithms, machine learning, and a robust data ecosystem, the team helps advertisers achieve their goals while driving Instacart’s revenue growth. By fostering a cycle of success for advertisers, they play a pivotal role in the company’s overall business success.

About the Job

We believe that high-quality data is essential for any business organization, as such we are looking for a strong software engineer excited to raise our efficiency, quality and scalability bar. You will be able to have extensive ownership and the ability to help set best practices and contribute to product and infrastructure features. 

As a craft leader, you'll be responsible for contributing to the vision, strategy and development of our multi-platform reporting system that is efficient, scalable, and meets diverse user needs. You will advocate for data quality, correctness, scalability and latency standards to ensure consistency in how we enable data-driven decisions and features across the organization. 

You will also be proactive in spearheading new initiatives, coding and documenting components, writing and reviewing system design documents and partnering with other teams and functions to gather and understand our customer's requirements. You will think and plan strategically for short and long term initiatives to continue shaping our platform and products.

About You

Minimum Qualifications

• Bachelor's degree or higher in Computer Science, Software Engineering, or a related field, or equivalent proven industry experience (4+ years).
• 5+ years of experience in software engineering.
• Comprehensive understanding of distributed systems, proven experience with data processing technologies such as DBT and Airflow and common web frameworks such as Rails.
• Highly proficient with SQL, capable of writing and reviewing complex queries for data analysis and debugging.
• You can design for scale with the entire system in mind.
• Solid communicator, comfortable seeking and receiving feedback.
• Strong analytical and debugging skills.
• Strong sense of ownership working with a large codebase and diverse suite of products.
• A collaborative mindset to be able to partner with engineers, designers and PM's from multiple teams to co-create impactful solutions while supporting system contributions.
• Strong organizational skills with the ability to communicate and present ideas clearly and influence key stakeholders at the manager, director, and VP level.

Preferred Qualifications

• Prior work experience in the digital advertising industry.
• Experience with big data technologies such as Spark, Hadoop, Flink, Hive or Kafka, and with both streaming and batching data pipelines.
• Proven experience with distributed system design.
• Strong general programming and algorithm skills.
• Strong attention to detail and accuracy in the implementation, keen eye for edge cases and code reviews. 
• Data driven mindset.

#LI-Remote

We are looking for a Data Platform Engineer to join our Data Engineering team and help build the foundational systems that power Figma’s next generation of AI-driven products and data experiences.

This is a unique opportunity to be an early engineer shaping Figma’s ML and data platform, enabling everything from self-serve analytics to production-grade AI systems. You’ll work at the intersection of data, infrastructure, and machine learning, building scalable systems that empower Data Science, unlock AI capabilities across the company, and bring data and models closer to the product experience.

This is a full-time role that can be held from one of our US hubs or remotely in the United States.

What you’ll do at Figma:

• Lead work on Figma’s AI data agent to enable self-serve analytics by owning the data-agent layer, building prompt-processing pipelines, instrumenting interactions, and delivering prompt-based usage analytics
• Own and evolve Figma’s ML and data platform, including model serving, feature pipelines, workflow orchestration, CI/CD for models, and production monitoring
• Build product-facing data systems and data products so models and data become first-class components of Figma’s product experience
• Ship platform tooling that enables Data Science teams to deploy, iterate on, and operate models effectively, including feature stores, rollout systems, and observability
• Design and scale infrastructure for AI-assisted and natural language interfaces to data, unlocking self-serve analytics across the company
• Drive cross-functional platform initiatives, aligning data contracts, SLAs, and system design across Data Science, AI/ML, Infrastructure, and Product
• Improve the developer experience for ML and data practitioners through robust abstractions, tooling, and platform capabilities

We’d love to hear from you if you have:

• 5+ years of experience in data platform, infrastructure, or machine learning engineering, with at least 1+ years working on AI or ML systems
• Experience building and operating end-to-end ML systems in production (training, evaluation, deployment, monitoring)
• Strong programming skills in Python or a similar language, with proven ability to build reliable, scalable systems and services
• Experience designing ML infrastructure (model serving, feature pipelines, workflow orchestration) and scalable system architectures
• Proven ability to work cross-functionally and drive projects across Data Science, Engineering, Infrastructure, and Product, with experience in data modeling and data product design

While it’s not required, it’s an added plus if you also have:

• Experience with ML platform tooling such as MLflow, Kubeflow, feature stores, or CI/CD for ML workflows
• Familiarity with LLMs, RAG systems, prompt processing, or AI-native infrastructure
• Experience building self-serve analytics platforms or internal data tools
• Experience with modern data stack technologies such as Snowflake, dbt, or Dagster, and cloud platforms such as AWS
• A strong product mindset and interest in connecting platform work to user and business impact

At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Compensation Ranges:

L3 - Tier 1 City: $135,000 - $165,000 CAD
L3 - Tier 2 City: $115,000 - $140,000 CAD

Leveling & Location:

Thanx uses structured internal levelling and location-based compensation. Final levelling and compensation are determined through the interview process based on experience, scope, and work location, and any offer will align to the appropriate range.

Application Process:

• This position is a new role.
• We may use artificial intelligence (AI) tools to assist in screening or assessing applications; human review will always remain part of the process.

Ready to change your life? Apply now!

We are proud to be an Equal Employment Opportunity company. We do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Thanx will consider qualified applicants with arrest or conviction records for employment in a manner consistent with local requirements.