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 You will design modern data orchestration solutions utilizing Apache Airflow, dbt, and Kafka to replace outdated batch processing with real-time, event-driven flows.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

#P24079_3413893

About the role

Are you passionate about using data to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field.

Salary Range

Toronto: the pay range for this role is $171,000 to $235,500 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About the role

Are you passionate about using data to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field.

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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.

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

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.

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.

About the role

Are you passionate about using data and AI to shape the future of Faire's Go-to-Market (GTM) strategy, sales, and operations? If so, we want to talk to you! We're looking for a technical owner in our team to work closely with Revenue Operations, GTM Systems Engineers, Data Scientists, Product Analysts and Software Engineers to support revenue-driving GTM initiatives by designing and building scalable data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve GTM data consumption workflows (e.g., Snowflake, BI tools, Salesforce), and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly. 

Join us and be part of a team that values data-driven innovation and excellence.

What You Will Do

The ideal candidate will possess a perfect blend of data engineering technical expertise and the product sense to be able to translate internal customer needs into practical solutions. They will have strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on GTM data initiatives. 

• Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.
• Lead the technical execution in building scalable data models and pipelines for a GTM domain defining the architecture, data requirements, and roadmap (e.g., Contact Scoring, Lead Qualification, Sales Pipeline, Sales Enablement).
• Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.
• Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows.
• Optimize processes for operational excellence in project management and system reliability.
• Ensure security standards are met within data systems and workflows. 
• Ensure and promote data quality standards for accurate and reliable insights.
• Embrace emerging technologies with enthusiasm.

Minimum qualifications

• 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.
• Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
• Production-level development experience in Python.
• Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
• Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
• Experience with Airflow, Docker, DBT or similar analytics workflow tools.
• BA/BS degree in Computer Science, Math, Physics, or a related technical field. 

Nice-to-haves

• Experience with GTM specific data modeling using a BI tool such as Looker or similar while leveraging conversational analytics. Build and own the GTM semantic layer.
• Hands-on experience with GTM-specific data and platform apps, including Reverse ETL (e.g., Hightouch), ELT/Ingestion tools (e.g., Fivetran), iPaaS/Integration platforms (e.g., Workato, N8N, Zapier), and CRM/GTM systems and tool (e.g., Salesforce, Clay).

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Hey there! We’re ContactMonkey 👋

Our mission? To power measurable employee engagement worldwide. And we’d love for you to join us!

About the job - AI Architect 

ContactMonkey's platform already runs AI in production - Claude-powered template editing, a standalone ConfidenceCheck service that evaluates outgoing emails for editorial quality and link safety, Braintrust-backed evaluations, and per-organization feature gating. The next wave is bigger: grounded assistants, retrieval over customer brand and campaign history, richer agentic flows inside the composer, and data products that make sending decisions smarter.

We're forming a dedicated AI pod to own that trajectory. With the team you will be setting the technical direction for the pod, make the foundational infrastructure bets (vector store, evals, data warehouse, agent orchestration), and ship the first production systems yourself. This is an architect role in the sense that you own the shape of the thing - it is not a role where you stop writing code.

Your impact

• AI platform direction: Model selection and routing, prompt and context architecture, evaluation strategy, cost and latency budgets, safety and PII handling. Decide where we go deeper with frontier models, where we fine-tune smaller ones, and where classical ML beats an LLM.
• Retrieval and grounding infrastructure: You'll pick it, design the ingestion path (brand kits, past campaigns, template library, per-org knowledge), own the chunking/embedding/refresh strategy, and set the quality bar via evals.
• Agent and tool-use patterns: Multi-turn tool-calling loops, deterministic fallbacks, observability, recoverable failure modes across Sidekiq and SQS, human-in-the-loop checkpoints where they matter.
• Data engineering foundations: You'll decide whether we need a warehouse (BigQuery / Snowflake / DuckDB-on-S3/ RedShift), design the pipelines that feed both product analytics and model training/eval datasets, and make sure the lineage is clean enough that we trust what we ship. Build a foundation for the next level data analytics across the company.
• Cloud and deployment architecture: We run on AWS (ECS, S3, SQS etc). You'll make the calls on how AI services are deployed - when a new microservice like ConfidenceCheck is the right pattern vs. embedding in the Rails monolith, how we handle GPU/accelerated inference if we ever need it, how we isolate model spend per tenant.

What we expect from you technically

You should be credible across all four of AI, Cloud, Data, and Fullstack - not a specialist in one with passing knowledge of the others. 

Concretely:

AI / ML

• Built and operated LLM-backed features in production against real users.
• Deep familiarity with at least one major provider SDK (Anthropic, OpenAI) and comfort switching between them. Understand prompt caching, structured outputs, tool use, and the tradeoffs between agent loops and pipeline-style orchestration.
• Evals are a reflex, not an afterthought. You've run a real eval harness (Braintrust, promptfoo, in-house) against golden datasets and used it to block regressions.
• Working knowledge of retrieval systems: embeddings, hybrid search, reranking, and where each breaks. Opinions on pgvector vs. dedicated vector DBs and when either is wrong.
• Bonus: fine-tuning or distillation experience, classical ML for ranking/classification, prompt-injection and jailbreak threat modelling.

Cloud

• AWS fluency at the architecture level - VPCs, IAM boundaries, secrets management, queue-based decoupling, cost control. Equally comfortable if we need to run a workload on GCP for a specific reason.
• Container-native deployment (ECS, EKS, or equivalent). IaC experience (Terraform or CDK) - even if we aren't using it yet, you should expect to bring it in.
• Have operated production systems under real load. You've been paged, and you've written the postmortem.

Data Engineering

• Can design a data pipeline end-to-end: ingestion, transformation, storage, serving. Batch and streaming. Have built this in at least one real organization.
• Comfortable with SQL and non SQL at a level that lets you reason about query plans, not just write queries. You've tuned a slow query by looking at the plan, not by guessing.
• Opinion on when a warehouse earns its keep vs. when read replicas are enough. We're at that decision point.
• Bonus: dbt, Airflow / Dagster / Prefect, CDC patterns, multi-tenant data partitioning at scale.

Fullstack

• Our backend is Ruby 3.4 on Rails 7.2 with Sidekiq Pro and SQS; our frontends are Vue 3 (main app), Nuxt 4 (recipient-facing content), and a Fastify/TypeScript AI microservice. You don't need all of this on day one, but you should be a polyglot who ramps quickly.
• Write real TypeScript. The AI-adjacent services are TS-first and that is likely to grow.
• Understand API design past the happy path - versioning, auth modes (we run session auth for the main API and bearer tokens for integrations), rate limiting, idempotency.

What we bring to the table 

🏥 100% employer-paid benefits + a Health Spending Account from day one

🌎 Work from anywhere in the world for up to 4 weeks

💰 Stock option plan—own a piece of our success

💲 RRSP Group Savings Plan to plan for your future

🏝 Generous vacation package to recharge and relax

📚 Personal development budget to fuel your growth

🧖 One personal day + two volunteering days to give back

🎂 Your Birthday off—celebrate on us!

🍎 Five health days per year to stay at your best

💼 Beautiful downtown Toronto office for hybrid work—fully stocked with all the best snacks

Compensation & Work Details

Compensation is thoughtfully determined based on your experience, skill set, and alignment with our internal compensation framework and internal equity.

We’re always happy to answer questions about compensation throughout the hiring process.

This is a net new position based out of our downtown Toronto office, at King and Spadina. Our engineering team works primarily remote but we are looking for someone who is willing to come into the office occasionally on an as needed basis.

Who We Are 

Imagine being part of a team of brilliant minds, all shaping the future of workplace communication. Here at ContactMonkey, we’re not just sending out traditional emails with our internal comms software; we’re changing the way companies connect and communicate with their people. Brands like IKEA, Roku, KMPG, and countless others are using our solution to transform employee engagement.

Our all-in-one platform—featuring a drag-and-drop email builder, engagement tools, and analytics—makes it easy for businesses to create, send, and measure their internal email campaigns directly within Outlook or Gmail. This way, internal communications go from being ignored to binge-worthy, sparking more opens, clicks, and conversations.

We’ve been on an explosive growth streak over the past few years, and we’re not slowing down anytime soon. Here’s a bit of what we’re proud of:

• Ranked by the Globe & Mail as one of Canada’s fastest-growing companies
• Recognized in 2023, 2024 and 2025 Deloitte Technology Fast 50™ awards for revenue growth over the past four years
• Recognized in 2023, 2024 and 2025 Deloitte Technology Fast 500™ as one of the fastest-growing companies in North America
• Raised $55 million Series A financing in 2023

Diversity is our strength

At ContactMonkey, we are building diverse products and we need a diverse team to do that. We strongly encourage applications from everyone regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status. 

We are committed to creating an accessible experience for all candidates. If you require any accommodations or adjustments during the interview process or beyond, please inform us, and we will work with you to ensure the necessary support is in place. We are continually striving to enhance our accessibility practices and welcome any feedback or suggestions on how we can better serve candidates with accessibility.

AI Disclosure: 

We use AI to take notes during our interview. Applications and interviews are reviewed by our Talent Acquisition team. Our applicant tracking system utilizes AI for workflows and hiring process efficiencies.

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

About this role:

Our Engineering organization owns the software that makes our marketplace work. The Platform group empowers teams across Faire: Product Engineering, Data Science, Product Management, Strategy, Analytics, Finance, etc. Enabling these functions to do their best work without concern about underlying infrastructure. We enable product engineering teams to build and operate software with unmatched speed and quality. We care about good engineering practices, excellent developer experience, security, testability, ease of maintenance, and scaling to serve millions of users. We value best practices to achieve excellent availability and performance.

The Analytics Platform team builds capabilities to accelerate data-driven analytics, improve productivity and accuracy at Faire. Its mandate is to reduce time from data to insights.

The team focuses on the following areas and capabilities:

• Data warehousing optimization, including performance, efficiency, cost
• Capabilities for data quality, metadata enrichment, lineage, privacy
• Tooling and capabilities to accelerate productivity of analytics subject matter experts; automation of analytics functions
• Development patterns and practices for foundational assets
• Elements of data security, privacy, and governance

The team also owns relationships with select infrastructure vendors.

We’re looking for:

• An experienced analytics engineer to work alongside our highly talented team, develop and deliver technical projects, and engage with other teams in the organization.

What you’ll do:

• Partner with key internal customers of the analytics function across business verticals, Strategy, Finance, others to develop capabilities based on their needs
• Improve development patterns and guide the broader analytics function on evolution of foundational datasets
• Lead technical execution in building scalable data models and pipelines for key domains, defining architecture, feature requirements, roadmaps
• Tackle challenges of data quality, integrity, relevance, and other analytics related concerns, for accurate and reliable insights
• Plan and execute on technology projects that scale with our growth; contribute to our architecture with a focus on analytics
• Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals.
• Provide technical guidance and mentorship on difficult open-ended problems.

Qualifications:

• Strong SQL and Python skills and demonstrated competencies in designing well-architected data models and optimizing query performance
• Experience building and evolving platform / foundational datasets and enabling other business functions that consume them
• Analytics engineering experience with a focus on data modeling, large-scale data processing, and tool development for analytics or data science use cases
• Experience with Airflow, dbt or similar analytics workflow tools; Snowflake experience especially valuable
• Knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms
• Data warehousing experience at Petabyte scale
• Understanding of performance, capacity, cost trade-offs in data processing systems
• Strong communication skills
• A bachelor's degree in Computer Science / Engineering or equivalent industry experience

Technologies we use and teach:

• AWS
• Snowflake
• Airflow
• Spark
• Python
• Kotlin

Salary range:

Canada: the pay range for this role is $160,000 - $220,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

As the GTM Engineer at 7shifts, you’ll build the technical engine behind our global marketing and sales strategy, transitioning our motions from manual one-size-fits-all campaigns to an intelligent system that triggers the right action at the right moment. Reporting to the Senior Manager, GTM Data Science & Engineering, your focus will be on building internal products and automated workflows that drive results across acquisition, retention, and expansion. As a strategic technical partner to go-to-market teams, you will engineer seamless experiences that turn complex data into business value at scale.

What you’ll do:

• GTM Tool Building: Build internal products that replace manual research with automated intelligence, enabling teams to shift from generic marketing and sales motions to personalized, data-backed approaches.
• Data Acquisition & Signal Engineering: Engineer workflows that blend vendor data with custom signals to identify high-value prospects based on specific triggers and market events across GTM initiatives.
• Targeting & Prioritization: Replace manual list-building with data-driven prioritization models, ensuring resources are focused on the prospects and growth opportunities with the highest probability of conversion across the funnel.
• AI Agents & Workflows: Deploy AI agents to automate routine tasks, increasing organizational capacity and enabling teams to maintain high-quality decision making across workflows.
• Lifecycle Orchestration: Orchestrate cross-functional GTM motions using event-driven triggers, ensuring that interactions are synchronized with real-time behaviour to improve engagement timing and relevance.
• Data Pipelines & Activation: Establish a centralized GTM logic layer within the data warehouse to ensure all execution platforms operate from a unified source of truth, maintaining data integrity across initiatives.
• Cross-Functional Enablement: Serve as a strategic bridge between GTM and Data teams, translating business goals into technical requirements and enabling stakeholders to effectively apply data to optimize their core motions.

What you bring:

• 2+ years of experience in Analytics Engineering, Marketing Analytics, Growth Engineering, Revenue Operations, or a similar role. You understand the technical side of acquisition, retention, and expansion.
• Advanced proficiency in SQL and Python or JavaScript. You are comfortable building lightweight internal tools, custom scripts, and managing complex data transformations.
• Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery) and dbt for managing business logic and ensuring data quality.
• Deep understanding of APIs and the ability to architect data flows between disparate GTM tools (Salesforce, Braze, etc).
• The ability to act as a strategic bridge, translating high-level business goals into technical specs while helping non-technical stakeholders operationalize data signals.
• A business-first engineering mindset. You think end-to-end  from raw data extraction to activation, focusing on revenue impact rather than just shipping code.
• Experience integrating LLMs into production environments for tasks like unstructured data extraction, lead qualification, or building autonomous agentic workflows.

It’d be even cooler if you had:

• Experience working with Snowflake or Snowflake data
• Knowledge of restaurant operations/sector
• Product-led Growth (PLG) experience

This role is an existing vacancy and is part of our current hiring plan. 

Compensation

The base compensation range for this position is CAD $92,000 - CAD $130,000. This range reflects the full growth path for the role, from building core skills to accomplished performance, through to role mastery. We typically target the accomplished level when hiring externally. At this level, individuals bring relevant experience in the role, demonstrate strong job-related skills, operate with confidence and consistency, and are able to deliver impact with limited ramp-up while still having meaningful opportunity to grow.

Compensation at 7shifts is performance and growth-driven. As you develop your skills and expand your impact over time, your compensation grows with you. Your specific placement within this range is based on your job-related skills, knowledge, and experience, as well as our internal equity assessment. We are always happy to discuss our approach throughout the hiring process.

Who We Are

Konrad is a next generation digital consultancy. We are dedicated to solving complex business problems for our global clients with creative and forward-thinking solutions. Our employees enjoy a culture built on innovation and a commitment to creating best-in-class digital products in use by hundreds of millions of consumers around the world. We hire exceptionally smart, analytical, and hard working people who are lifelong learners.

About The Role

As a Data Engineer you’ll be tasked with designing, building, and maintaining scalable data platforms and pipelines. Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure reliable, secure, and efficient data solutions.

What You’ll Do

• Design, build, and manage robust data pipelines and data architectures.
• Implement solutions leveraging platforms such as Azure Fabric, Databricks, and Snowflake.
• Optimize data workflows, ensuring reliability, scalability, and performance.
• Collaborate with internal stakeholders to understand data needs and deliver tailored solutions.
• Ensure data security and compliance with industry standards and best practices.
• Perform data modelling, data extraction, transformation, and loading (ETL/ELT).
• Identify and recommend innovative solutions to enhance data quality and analytics capabilities.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.
• At least 3 years of professional experience as a Data Engineer or similar role.
• Proficiency in data platforms such as Azure Fabric, Databricks, and Snowflake.
• Hands-on experience with data pipeline tools, cloud services, and storage solutions.
• Strong programming skills in SQL, Python, or related languages.
• Experience with big data technologies and concepts (Spark, Hadoop, Kafka).
• Excellent analytical, troubleshooting, and problem-solving skills.
• Strong understanding of data modeling concepts including medallion architecture, data vault, grain, fact tables, dimensions, and schema design.
• Hands-on experience building and maintaining transformation layers using dbt or similar ELT tools.
• Experience building production-grade data models with optimized performance supporting operational decision-making.
• Experience designing batch and real-time ingestion frameworks with real-time monitoring
• Ability to effectively communicate technical concepts clearly to non-technical stakeholders.

Nice to have

• Certifications related to Azure Data Engineering, Databricks, or Snowflake.
• Familiarity with DevOps practices and CI/CD pipelines.

Perks and Benefits

• Comprehensive Health & Wellness Benefits Package
• Retirement Planning
• Parental Leave Program
• Flexible Working Hours
• Work from Home Flexibility
• Service Recognition Programs
• Socials, Outings & Retreats
• Culture of Learning & Development

Bonus Points

Have you taken any courses at BrainStation? A lot of our design and development best practices and processes are taught during our courses - make sure to highlight this experience in your cover letter if you have!

Konrad is committed to maintaining a diverse work environment and is proud to be an equal opportunity employer. All qualified applicants, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status will receive consideration for employment. If you have any accessibility requirements or concerns regarding the hiring process or employment with us, please notify us so we can provide suitable accommodation.

The estimated compensation for this position is $90,000 to $125,000. This is an estimate and a compensation offer will vary based on applicant’s education, experience, skills, abilities and alignment with market data.

While we sincerely appreciate all applications, only those candidates selected for an interview will be contacted.

#LI-Hybrid

The role

Benefits

product initiatives where leverage is highest.

This is a high-ownership role with real business responsibility, not a feature factory position.

What you’ll own

Smart Fridges (Primary)

• Own the end-to-end product strategy and execution for Smart Fridges (hardware, software, ops, and UX).
  
  
• Define and prioritize the roadmap across:
• Fridge software
• Hardware & IoT flows
• Computer vision, inventory, and ordering logic
• Operational workflows (installations, refills, failures, edge cases)
  
  
• Partner closely with engineering, design, ops, data, and clients.
• Drive outcomes across conversion, retention, reliability, and unit economics.
• Be accountable for shipping, learning, and iterating fast in a real-world, non-perfect environment.

Partnerships & Integrations

• Lead product ownership of strategic integrations (external partners, platforms, APIs).
• Translate partnership agreements into clear product requirements and technical scopes.
• Work with internal teams and external partners to ensure:
• Clean integrations
• Scalable flows
• Clear ownership and SLAs
• Identify opportunities to turn integrations into growth or retention levers, not just technical connections.

Cross-cutting / General Product Support

• Help bring structure to ambiguous or fast-moving initiatives.
• Act as a force multiplier for the product org: unblock, simplify, and push things forward.

What success looks like

• Smart Fridges has a clear backlog, fewer fires, and measurable improvements in key metrics.
• Integrations ship faster, with less ambiguity and fewer surprises.
• External partners feel aligned and confident working with us.
• Teams have clarity on what we’re building, why, and what success means.
• Leadership trusts you with increasingly complex and strategic problem spaces.

What we’re looking for

Must-haves

• 4+ years of experience as a Product Manager.
• Proven experience owning complex systems (multi-team, multi-stakeholder).
• Strong ability to operate in ambiguity and bring structure.
• Excellent written and verbal communication.
• Comfortable working across engineering, design, ops, and external partners.
• Business-minded: you care about outcomes, not just shipping features.

Strong plus

• Passion for the healthcare and food-is-medicine industry.
• Experience with hardware, IoT, marketplaces, or logistics-heavy products.
• Experience with integrations, APIs, or platform products.
• Experience working with partnerships or external vendors.
• Startup or high-growth environment experience.

Why is this role interesting?

• You’ll work on a rare mix of hardware + software + ops + partnerships.
• You’ll have direct exposure to leadership and real influence on product direction.
• You’ll help scale products that exist in the physical world, with real constraints and real impact.
• This role can grow significantly as the product surface area expands.

Benefits

💸 Get paid in USD

🗺 Work remotely: design the life that you want

⛱ Enjoy 15 days of vacation each year from the start date

🎄 16 fully paid Argentinean holidays

🩺 Healthcare Benefit: Monthly stipend to use in your preferred healthcare provider

🗓️ 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

🧘🏽‍♀️ Flexible benefits, your way: a prepaid card you can use on wellness, learning, food, and more.

🤖 AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

🧑‍🏫 Personalized English coach

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 

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!

About this Role

We're looking for a Senior Data Systems Engineer who bridges the gap between hardware domain expertise and modern data infrastructure. You won't just build pipelines — you'll work directly with foundries, OSATs, test engineers, and validation teams to understand what the data means, define how it should flow, and build the platform that makes AI-driven decisions possible across 13+ active hardware programs.

This is not a typical data engineering role. The right person has a background in semiconductor manufacturing, photonics, hardware test/validation, or a related hardware discipline — and a strong pull toward data systems, process optimization, and automation. You understand that the hardest part of a data platform isn't the code; it's knowing which data matters and why.

What You'll Do

Program Data Onboarding & Vendor Engagement

• Engage directly with foundries, OSATs, and internal engineering teams to align on data formats, delivery mechanisms, and quality standards for new programs
• Own the data onboarding lifecycle for programs ramping to High Volume Manufacturing (HVM)
• Identify gaps in data coverage across the pipeline: design, foundry, test/validation, photonics characterization, packaging/assembly, and system-level validation
• Influence external and internal teams to adopt scalable, platform-compatible data practices — this is hands-on stakeholder work, not email coordination

Data Platform Engineering

• Design, build, and maintain data pipelines that ingest, transform, and deliver hardware data from wafer-level test through system validation
• Build and maintain data models in dbt on Snowflake that serve downstream analytics, reporting, and AI/ML workflows
• Develop and operate orchestration workflows (Dagster) for reliable, observable data delivery
• Implement data quality checks, monitoring, and alerting to ensure platform reliability across production programs

Performance Metrics & Reporting

• Build performance metrics pipelines that translate raw hardware data into actionable insights for engineering and program teams
• Own stakeholder reporting and deliver training for teams onboarding to platform tools (Snowflake, Sigma, custom dashboards)
• Support AI/ML workflows by ensuring the data foundation is clean, structured, and reliable

Platform Improvement & Tooling

• Contribute to platform infrastructure: CI/CD, RBAC, cost optimization, self-service tooling
• Participate in sprint ceremonies, contribute to architectural decisions, and help shape the team's technical roadmap
• Mentor junior team members on both data engineering practices and hardware domain context

What You Bring

Required

• Bachelor’s Degree in Photonics, Data Engineering, Electrical Engineering or a related field
• 8+ years of professional experience in data engineering, process engineering, test engineering, or a related technical role in semiconductor, photonics, or hardware manufacturing
• Proficiency in Python and SQL
• Experience with Snowflake, dbt, Dagster/Airflow, or similar modern data stack components
• Experience working with data for hardware test, manufacturing, or characterization systems
• Demonstrated ability to work cross-functionally with technical teams and external partners (vendors, foundries, or OSATs) to define data requirements and influence practices
• Strong analytical thinking — you can look at a dataset and understand what it means in the physical world, not just how to transform it

Preferred

• Master’s or PhD in Physics, Electrical Engineering, Photonics, or a related field with 4+ years of experience
• Background in silicon photonics, photonic integrated circuits (PICs), or optical systems
• Experience with High Volume Manufacturing (HVM) ramps or new product introduction (NPI) data workflows
• Familiarity with semiconductor test data formats (STDF, WAT, parametric data)
• Experience building data quality frameworks or monitoring systems
• Experience with AI/ML tools applied to manufacturing or engineering data

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

WHAT YOU’LL DO

Join our passionate Business Intelligence Engineering team focused on building and maintaining robust data pipelines and products that enable better decision-making across Braze. You’ll work alongside talented engineers and stakeholders across the business to support data infrastructure, develop reliable metrics, and implement data processes that scale with our growth.

Responsibilities:

• Partner with stakeholders to clarify requirements and translate them into scalable data models, definitions of metrics, and sustainable dbt implementations
• Own and evolve the semantic layer alongside curated warehouse models: define reusable metrics and dimensions
• Partner with analytics and data engineering on the metric lifecycle (definition, approval, deprecation), documentation, and lineage from semantic objects through to downstream consumers
• Raise the bar on data quality: design and maintain tests, monitoring to keep metrics consistent as the business scales
• Design and communicate data flows, dependencies, and SLAs for your areas; coordinate with Data Engineering and platform teams where orchestration, warehouse behavior, or access patterns affect reliability or cost
• Mentor engineers and analysts through code review, pairing, and shared standards so the whole BI engineering practice ships faster with fewer incidents

WHO YOU ARE

The ideal candidate for this role possesses:

• 5+ years of experience in business intelligence, analytics engineering, or data engineering, with substantial time on cloud data warehouses and SQL-first analytics engineering
• Expert-level SQL and strong data modeling skills and metric design that survives real-world edge cases
• Deep hands-on experience with dbt (projects, packages, tests, documentation, CI-oriented workflows) and Snowflake (or a comparable warehouse), including optimization and operational awareness
• Hands-on experience building or maintaining a semantic layer—modeling metrics and dimensions for governed consumption, with clear documentation, drill and aggregation behavior, and access patterns suited to both self-serve and curated reporting
• Familiarity with orchestrated pipelines (for example Airflow or similar) and how upstream freshness and quality affect downstream marts and metrics
• Excellent communication with technical and non-technical partners; ability to prioritize, push back constructively, and anticipate downstream impact of model and metric changes

For candidates based in Ontario, the pay range at the start of employment for this position is expected to be between CA$112,000 - CA$168,000/year, with an expected On Target Earnings (OTE) between CA$128,000 - CA$193,000/year (including performance-based or variable compensation (bonus or commission). Your particular offer may vary depending on multiple individual factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

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

Analytics Engineer   

We are seeking an experienced Analytics Engineer to join our Data Solutions team in North America. This role will combine technical expertise with strategic vision to drive the adoption and optimization of Sigma across our client base and internal teams.  

Ideal candidates will be able to:  

• Lead the development and implementation of visualizations that communicate complex data analyses to non-technical audiences showcasing best practices and innovative approaches using tools such as  

• Establish and manage the Business Intelligence Center of Excellence, creating standards, guidelines, and training materials  

• Collaborate with cross-functional teams to design and implement data solutions that align with client business objectives  

• Manage the analytics engineering and visualization lifecycle, including research, proof of concepts, architecture, design, development, testing, and maintenance  

• Generate visualizations that communicate complex data analyses to non-technical audiences  

• Partner with client stakeholders to foster the adoption of best data management practices  

• Mentor and develop junior team members  

• Support sales cycles by leading scoping discussions and building proof of concept solutions  

• Stay current with Business Intelligence tools and visualizations updates and industry trends, sharing knowledge across the organization  

Qualifications:  

• 5+ years of experience in data analytics, business intelligence, or related field  

• 2+ years of experience in Sigma Computing with advanced proficiency in other tools such as PowerBI, Looker, Omni etc  

• Strong SQL skills and experience with cloud data platforms (e.g., Snowflake, Azure, AWS)  

• Experience with modern data stack tools such as dbt, Fivetran, Matillion, or similar  

• Familiarity with Python and other programming languages used in data analysis  

• Understanding of data architecture, data warehousing, and ETL/ELT processes  

• Excellent communication and presentation skills, with the ability to explain complex concepts to non-technical audiences  

• Experience in consulting or client-facing roles  

• Track record of successful project delivery using Agile methodologies  

Personal Qualities:  

• Passionate about data and its potential to drive business value  

• Strong leadership and mentoring abilities  

• Proactive problem-solver with a results-oriented mindset  

• Adaptable and eager to learn new technologies and methodologies  

• Excellent interpersonal skills with a people-first mentality  

Join us in revolutionizing how businesses leverage Sigma and analytics to drive success!  

Software Engineer, Financial Systems

Team: IT, Security, and Corporate Engineering
Location: Toronto

About the Role

At Opendoor our goal is to build the biggest, most trusted housing platform and set a new standard for how people move. We've combined our deep, proprietary data and operational expertise with the power of artificial intelligence to make online home selling and buying radically simple.

We are eliminating the manual work that slows down operations.  We’re building AI-driven automation that closes the books faster, eliminates repetitive workflows, and gives Finance teams real-time insights without human intervention.  You’ll architect the systems that power thousands of real estate transactions monthly with audit-ready precision while enabling Finance to move fast and operate efficiently.

What You'll Do

• Build intelligent automation that eliminates manual financial workflows, from journal entries to reconciliations to month-end close processes, using AI agents and workflow orchestration.
• Design and own integrations connecting enterprise resource planning (ERP), spend management, banking, and data warehouse systems that power real-time financial operations.
• Partner with Finance, Procurement, Accounting, Accounts Payable and Capital Markets stakeholders to understand their workflows, identify automation opportunities, and deliver software solutions that increase their speed and efficiency.
• Implement observability, monitoring, and reliability practices for production financial data systems that process millions of transactions daily.
• Apply software engineering best practices (CI/CD, Infrastructure as Code, automated testing, code review) to financial systems traditionally managed through manual configuration.

Tech Stack

• Financial Platforms: NetSuite (ERP), Ramp (spend management), bank APIs
• Data & Analytics: Snowflake, dbt, Airflow/Dagster, Quicksight
• Languages: Python, Go, SQL, TypeScript/Node.js
• Infrastructure: AWS, Terraform, Docker, GitHub Actions
• AI & Automation: LLMs (Claude, OpenAI), agent frameworks, workflow orchestration

What You'll Need

• Deep conviction that AI and automation should eliminate manual work humans shouldn't be doing anyway. You're excited to eliminate manual work by replacing spreadsheets and close processes with automated systems.
• 8+ years of software engineering experience with strong skills in Python, Go, or similar languages, including API design, systems integration, and automation.
• Experience with modern data platforms (Snowflake or similar), SQL, and building reliable data pipelines.
• Strong experience with cloud platforms (AWS preferred) including CI/CD, Infrastructure as Code, and running production services.
• Proven problem-solving ability to understand complex business workflows, identify automation opportunities, and design elegant technical solutions
• Humility and genuine curiosity. You're as excited to automate journal entries as you are to architect distributed systems, and you see eliminating mundane work as deeply meaningful engineering. You genuinely enjoy understanding user needs, partnering with non-technical stakeholders, and building software that makes their work easier.

Bonus Points For

• Experience with financial/ERP systems (NetSuite, Oracle, SAP, Workday) or fintech platforms.
• Understanding of financial concepts (General Ledger, Accounts Payable, month-end close, Sarbanes-Oxley controls).
• Track record building AI-powered automation, workflow orchestration, or internal tools.
• M.S. in Computer Science.

Compensation

Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

#LI-RO

As the Data Analyst, Finance at 7shifts, reporting to the Manager of Data & Analytics, you will act as a dedicated, embedded partner to our Finance team. You’ll serve as the strategic bridge between the central data function and the finance group, helping leadership measure what matters, uncover trends, and identify risks. Your expertise will guide the development of Finance-specific dashboards, forecast models, and automated reporting cadences that inform critical decisions. You’ll also be supported by a collaborative data team, including other analysts, analytics engineers, data engineers, and leaders, who work together to enable data-driven decisions across the company.

What you’ll do:

• Act as the primary, embedded data partner for the Finance team, participating in key cross-functional meetings to translate complex business questions into clear analytical frameworks
• Translate finance datasets into business narratives, proactively identifying patterns (e.g., Churn trends, Coupon Integrity) and leakages before they impact the bottom line
• Build, maintain, and own finance-specific dashboards, combining central "source of truth" data with finance-owned business logic 
• Automate and streamline data preparation for key operational cadences, including monthly business reviews, to reduce manual lift and increase speed to insight
• Develop and maintain data models using dbt and SQL to transform raw data into clean, reliable, and scalable datasets for analysis and reporting
• Maintain deep subject matter expertise on all core "finance data" definitions, tools, and roadmaps to ensure analysis is aligned with the central source of truth
• Effectively present findings and recommendations to both technical and non-technical audiences in a clear and actionable way

What you bring:

• Experience delivering financial analysis in support of finance teams
• Strong proficiency in SQL with the ability to write complex queries and work with large datasets
• Hands-on experience with BI tools such as Tableau, Looker, or Power BI (bonus if you’ve used Thoughtspot)
• Experience building and maintaining data models using dbt
• Background in business, analytics, or a technical field 
• Proven ability to collaborate effectively with cross-functional teams
• Strong communication and collaboration skills, with the ability to work with cross-functional teams and present data concepts to non-technical audiences
• Experience working in a SaaS with a deep understanding of key metrics such as ARR, Churn, and Net Revenue Retention

It’d be even cooler if you had:

• Worked with Snowflake or other cloud-based data warehouses
• Hands-on experience leveraging CRM (e.g., Salesforce) platforms and billing systems (e.g., Stripe) to understand the end-to-end customer lifecycle
• Previous experience in a finance data analyst role

This role is an existing vacancy and is part of our current hiring plan 

Compensation

The base compensation range for this position is CAD $78,000 - CAD $115,000. This range reflects the full growth path for the role, from building core skills to accomplished performance, through to role mastery. We typically target the accomplished level when hiring externally. At this level, individuals bring relevant experience in the role, demonstrate strong job-related skills, operate with confidence and consistency, and are able to deliver impact with limited ramp-up while still having meaningful opportunity to grow.

Compensation at 7shifts is performance and growth-driven. As you develop your skills and expand your impact over time, your compensation grows with you. Your specific placement within this range is based on your job-related skills, knowledge, and experience, as well as our internal equity assessment. We are always happy to discuss our approach throughout the hiring process.

Software Engineer, Financial Systems

Team: IT, Security, and Corporate Engineering
Location: Seattle, Washington

About the Role

At Opendoor our goal is to build the biggest, most trusted housing platform and set a new standard for how people move. We've combined our deep, proprietary data and operational expertise with the power of artificial intelligence to make online home selling and buying radically simple.

We are eliminating the manual work that slows down operations.  We’re building AI-driven automation that closes the books faster, eliminates repetitive workflows, and gives Finance teams real-time insights without human intervention.  You’ll architect the systems that power thousands of real estate transactions monthly with audit-ready precision while enabling Finance to move fast and operate efficiently.

What You'll Do

• Build intelligent automation that eliminates manual financial workflows, from journal entries to reconciliations to month-end close processes, using AI agents and workflow orchestration.
• Design and own integrations connecting enterprise resource planning (ERP), spend management, banking, and data warehouse systems that power real-time financial operations.
• Partner with Finance, Procurement, Accounting, Accounts Payable and Capital Markets stakeholders to understand their workflows, identify automation opportunities, and deliver software solutions that increase their speed and efficiency.
• Implement observability, monitoring, and reliability practices for production financial data systems that process millions of transactions daily.
• Apply software engineering best practices (CI/CD, Infrastructure as Code, automated testing, code review) to financial systems traditionally managed through manual configuration.

Tech Stack

• Financial Platforms: NetSuite (ERP), Ramp (spend management), bank APIs
• Data & Analytics: Snowflake, dbt, Airflow/Dagster, Quicksight
• Languages: Python, Go, SQL, TypeScript/Node.js
• Infrastructure: AWS, Terraform, Docker, GitHub Actions
• AI & Automation: LLMs (Claude, OpenAI), agent frameworks, workflow orchestration

What You'll Need

• Deep conviction that AI and automation should eliminate manual work humans shouldn't be doing anyway. You're excited to eliminate manual work by replacing spreadsheets and close processes with automated systems.
• 8+ years of software engineering experience with strong skills in Python, Go, or similar languages, including API design, systems integration, and automation.
• Experience with modern data platforms (Snowflake or similar), SQL, and building reliable data pipelines.
• Strong experience with cloud platforms (AWS preferred) including CI/CD, Infrastructure as Code, and running production services.
• Proven problem-solving ability to understand complex business workflows, identify automation opportunities, and design elegant technical solutions
• Humility and genuine curiosity. You're as excited to automate journal entries as you are to architect distributed systems, and you see eliminating mundane work as deeply meaningful engineering. You genuinely enjoy understanding user needs, partnering with non-technical stakeholders, and building software that makes their work easier.

Bonus Points For

• Experience with financial/ERP systems (NetSuite, Oracle, SAP, Workday) or fintech platforms.
• Understanding of financial concepts (General Ledger, Accounts Payable, month-end close, Sarbanes-Oxley controls).
• Track record building AI-powered automation, workflow orchestration, or internal tools.
• M.S. in Computer Science.

Compensation

The base pay range for this position is $198,000 - $271,000 USD annually, plus RSUs and bonuses. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

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 Data Analytics / Analytics Engineering professional to build and maintain our analytics data stack, deliver reliable insights, and empower teams across the company. You’ll play a key role in defining metrics, building scalable data models, and enabling self-serve analytics for multiple business functions.

What you’ll do

• Build, maintain, and optimize analytics data stack, including ELT pipelines, dimensional models, and semantic layers using dbt, Snowflake, and Airflow

• Collaborate with Marketing, Product, Operations, and Finance teams to define key metrics, improve reporting fidelity, and enable self-serve analytics

• Own and evolve core data models and pipelines that drive dashboards, reporting, and downstream analysis

• Apply best practices for data testing, observability, and CI/CD to ensure reliable, version-controlled, production-ready analytics code

• Partner with stakeholders to understand business needs and translate them into performant, trustworthy data products

• Contribute to internal data documentation and governance practices

• Mentor team members on data modeling, tooling, and processes, bringing a scalable, engineering-first approach to analytics

What we’re looking for

• 4–6 years of experience in analytics engineering, data analytics, or data engineering, ideally in fast-paced or high-growth environments

• Strong SQL expertise and experience with large-scale, normalized, or dimensional datasets

• Hands-on experience building data models with dbt in a production environment (CI, testing, documentation)

• Experience with cloud data warehouses like Snowflake, BigQuery, or Redshift

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

• Proactive communicator able to collaborate with business stakeholders and technical teams

• Strong ownership and accountability for data quality, performance, and maintainability

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

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: $110,000 - $140,000 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