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.

Lyft is looking for experienced software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our riders and drivers.

As a Software Engineer for Lyft Ads - you will work on one of Lyft’s newest lines of business focused on building the world’s largest transportation media network. We build products that allow brands to engage with our unique audience throughout their transportation journeys and beyond. For this role we are seeking software engineers who are passionate about backend and data engineering. You will join our Ad Infra Engineering team and contribute to building the systems and pipelines powering our ad-serving, measurement and audience platform. We work on technologies that let brands engage with our unique audience throughout their transportation journeys. This role is a great opportunity for an early-career engineer to gain experience working with distributed backend systems and large-scale data workflows, collaborating closely with product, analytics, and data science teams.

Why Lyft Ads?

• Be part of a high-impact team building the foundations of Lyft’s advertising infra
• Gain experience working with complex systems at scale, backed by mentorship and growth opportunities.
• Join a supportive, inclusive environment focused on engineering excellence and business impact.

Responsibilities:

• Develop and maintain backend systems that support real-time ad serving, campaign management, and reporting.
• Design and implement scalable data models to support analytics, targeting, and measurement use cases.
• Build and maintain data pipelines that handle ingestion, transformation, and distribution of large volumes of advertising data.
• Work with orchestration frameworks (e.g., Airflow) to schedule and monitor reliable, production-grade data workflows.
• Collaborate with cross-functional partners to integrate internal and third-party systems via APIs and batch data feeds.
• Write clean, maintainable, and testable code following best practices (CI/CD, observability, code reviews).
• Participate in architecture discussions and design reviews with an emphasis on performance and reliability.
• Learn and grow through mentorship, documentation, and regular team collaboration.

Experience:

• BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience
• 3+ years of industry experience in backend or data engineering roles
• Proficiency in at least one backend programming language (e.g., Python, Go, Java)
• Good understanding of distributed systems, microservices, and database design (SQL and NoSQL).
• Exposure to orchestration tools (e.g., Airflow, Prefect) and data distribution technologies (e.g., Kafka, Pub/Sub).
• Experience working with relational and non-relational databases (e.g., PostgreSQL, BigQuery, DynamoDB).
• Experience with Linux.

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 this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 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.

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

This job posting is for an existing vacancy.

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

Marqeta is looking for a talented Senior Software Engineer to independently identify and deliver software solutions on our Data Infrastructure team through a set of milestones spanning a specific platform focus or a multi-component system. You will own and deliver projects in service of quarterly goals on the team and independently identify solutions to solve ambiguous, open-ended problems. You will work in collaboration with your team and cross-functional partners.

The Data Infrastructure team, within our Data & ML Platforms organization, is responsible for the data lakehouse, streaming, orchestration, and catalog platforms that power analytics and AI across Marqeta. We're a platform engineering team building infrastructure that other engineering teams depend on.

At Marqeta, participation in a rotational on-call pager duty is a required part of the software engineering role. The specifics of the rotation may vary by team, depending on team size and structure, and will be discussed further during the interview process.

We work Flexible First. This role can be performed remotely anywhere within Ontario or British Columbia, Canada. We’d love for you to join us!

Learn more about our Product and Engineering team

The Impact You'll Have

• Define and deliver well-scoped milestones for projects, and may be a technical lead for projects on your team.
• Lead design for small-to-medium components and participate in design for larger components, moving from task-level impact to small-to-medium project-level impact.
• Have significant ownership of a component of the data infrastructure, including its reliability, performance, and developer experience.
• Identify gaps and propose plans towards addressing those gaps.
• Independently write code that is clear, well-tested, and appropriately flexible, reusable, and adaptable to changing requirements.
• Actively level up less-experienced members of your team by helping them with their craft, providing guidance, and setting a good example.
• Participate in on-call coverage.

Who You Are

• 5+ years of experience as a software engineer with a Bachelor's degree; or 3 years of experience with an advanced degree. In lieu of a degree, 8+ years of relevant experience may suffice.
• Strong proficiency in Python in a production context.
• Proficiency with SQL.
• Experience working with distributed systems.
• Production experience with multiple core data technologies, including Apache Kafka, Apache Spark, and Apache Airflow (or close equivalents).
• Production experience with modern table formats (Parquet, Hudi, Iceberg, or Delta Lake).
• Production experience with AWS or another major cloud.
• Experience with infrastructure-as-code (Terraform, CloudFormation, CDK, or equivalent).
• Experience monitoring and alerting on production systems.
• Ability to decompose business problems into solutions that may require designs with multiple interacting components.
• Ability to build correct, maintainable software components.
• Ability to work with cross-functional stakeholders to identify technical blindspots and clarify ambiguity.
• Ability to present clear and concise messages tailored to various audiences; able to communicate clearly and respectfully both verbally and in writing.
• A focus on quality and meeting deadlines.
• Ability to decompose business problems into solutions that may require designs with multiple interacting components.
• Ability to build correct, maintainable software components.
• Ability to work with cross-functional stakeholders to identify technical blindspots and clarify ambiguity.
• Ability to present clear and concise messages tailored to various audiences; able to communicate clearly and respectfully both verbally and in writing.
• A focus on quality and meeting deadlines.

Nice-To-Haves

• Experience with payments or the FinTech space.
• Experience with Apache Iceberg specifically.
• Experience with CDC tooling, particularly Debezium or Kafka Connect.
• Experience with data catalog tooling (DataHub or equivalent).
• Experience with Java in addition to Python.
• Exposure to Kubernetes and container-based workloads.
• Experience building scalable software platforms.

Our (typical) process:

1. Application Submission
2. Recruiter Video Call
3. Coding Interview & Hiring Manager Interview
4. Virtual “Onsite” consisting of three 60 minute rounds
5. Offer!

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD, is: 116,000 - 145,000

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

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.

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, including cost-efficient storage and compute
• ETL (extract, transform, load) and ELT (extract, load, transform) pipelines
• Evolution of foundational datasets with company-wide utilization
• BI (business intelligence) tooling and integrations
• Productivity acceleration tooling for analytics use-cases, including AI/LLM powered tools
• Automation of analytics functions
• Monitoring, alerting, and cost tracking for workloads
• Data security, privacy, and governance

The team also owns relationships with select infrastructure vendors.

We’re looking for: An engineer with data and analytics experience to work alongside our highly talented team, develop and deliver technical projects, and engage with other teams in the organization.

What you’ll do:

• Plan and execute on technology projects that scale with our growth; contribute to our technology foundations with a focus on data integrity, security, performance, scale, reliability, operational excellence.
• Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals.
• Provide technical expertise on difficult open-ended problems.

Qualifications:

• Strong Python and SQL skills
• Experience developing and operating ETL/ELT, storage, compute, workflow systems
• Exposure to building and operating reliable, scalable data pipelines, orchestration of data movement, querying, transformation, and frameworks for analytics engineering workflows
• Understanding of data warehousing basics, especially Snowflake, is highly valuable
• Understanding of performance, capacity, cost trade-offs in data processing systems. 
• Experience diagnosing, mitigating, and addressing data system production issues at scale
• Strong communication skills
• A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience

Select technologies we use and teach: AWS, Snowflake, Airflow, Spark, Python, Kotlin

Salary range:

Canada: the pay range for this role is $129,500 - $178,000 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.

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

About the Role:

We are looking for a Senior Software Engineer to architect, build, and maintain the data infrastructure at Gusto.  As part of the Data Platform team, you will collaborate closely with Data Science, Business Intelligence, and analysts across Gusto teams to help them achieve their goals. 

The Data Platform position is a software development role with knowledge of data architectures and data delivery. The ideal candidate is passionate about developing software, working with data, and

Here’s what you’ll do day-to-day:

• Architect, build, and refine our infrastructure and tools that enable other teams to work with data.
• Efficiently handle vast amounts of clickstream, database, and third party application data, processing in batch and real-time
• Take full ownership of the solutions you build, working with stakeholders to develop requirements, implement solutions, monitor production, and troubleshoot problems that arise.
• Work as part of a team. We value team players who share their knowledge and like collaborating with others.

Here’s what we're looking for:

• • At least 7 years of software engineering experience.
  • Experience building solutions in the cloud, AWS preferred (Redshift, MSK, EMR).
  • Experience with OLAP databases (Clickhouse)
  • Experience building data pipelines at scale, Airflow and Python preferred.
  • Experience with streaming systems desired (Kafka, Kinesis, or similar).
  • Ability to turn vague requirements into clear deliverables with minimal guidance.
  • Experience building and maintaining a modern data stack in production.

Our cash compensation amount for this role is targeted at $163,000-$204,000/year in Denver, $178,000-$223,000/year in Los Angeles, and $197,000-$247,000/year for San Francisco, New York, and Seattle. 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. 

The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. 

As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. 

Responsibilities:

• Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
• Evolve data model and data schema based on business and engineering needs
• Implement systems tracking data quality and consistency
• Develop tools supporting self-service data pipeline management (ETL)
• SQL and MapReduce job tuning to improve data processing performance
• Write well-crafted, well-tested, readable, maintainable code
• Participate in code reviews to ensure code quality and distribute knowledge
• Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions

Experience:

• Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field
• 4+ years of professional experience in data engineering, ideally with large-scale distributed systems.
• Strong skills in Spark, Python (or similar scripting language), and SQL performance tuning
• Experience with AWS, Hadoop/S3, Hive, Presto, Airflow, and related tools
• Solid understanding of ETL processes, workflow orchestration, and data warehousing
• A collaborative mindset—you’re comfortable working across teams to solve real-world problems

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.

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.

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.

 Our mission depends on having a digital representation of the physical world - a map with all routing related (real-time) information. This is what makes Lyft different from many products: our products don’t just facilitate online interactions, they facilitate dynamic, real-world ones. Without mapping services, none of these real world interactions between people and transport can happen.

We are hiring a Senior Data Engineer to join our Pickup, Places and Search team within the Mapping organization that is responsible for building, enhancing and maintaining the Rider and Driver product for the Pickup/Drop off Experience. This team supports the backbone of Lyft’s search system, supporting millions of rides by helping our riders and drivers connect and reach their destination. Our focus is to ensure the pickup/dropoff experience is seamless by enhancing guidance and routing as well as the rider experience. Additionally the team uses map data and other signals to create new product experiences in collaboration with teams across Lyft. This team has a history of enabling rich and creative features that directly influence the product for all of our users. We constantly innovate and incorporate cutting-edge technologies to make the lives of our community more enriched.

In this role, you'll collaborate with other engineering teams, product, data science, analytics, and operations on programs that empower us to iterate quickly, delighting our passengers and drivers with rideshare focused mapping experiences.

Responsibilities:

• Owner of core company data pipelines, responsible for scaling up data processing flow to meet the rapid data growth at Lyft
• Continuously evolve data models and schemas based on business and engineering requirements
• Implement and maintain systems to monitor and enhance data quality and consistency
• Develop tools that support self-service management of data pipelines (ETL) and optimize data processing performance
• Write well-crafted, well-tested, readable, maintainable code that prioritizes scalability and cost efficiency
• Conduct code reviews to ensure code quality standards and facilitate knowledge sharing
• Participate in on-call rotations to maintain high availability and reliability of workflows and data pipelines
• Collaborate with internal and external partners to remove blockers, provide support, and achieve results
• Help establish technical roadmaps and architectures based on technology and our business needs.
• Drive high-impact projects and innovate new solutions to provide the best mapping experience possible.
• Ship ML models at scale and low cost by focussing on systems / performance engineering.
  
  

Experience:

• 5+ years of relevant professional experience in data engineering or a related field
• Strong expertise in SQL and experience with Trino or Spark/PySpark
• Experience building and optimizing complex data models and pipelines with a strong understanding of ETL processes
• Expertise in data modeling and ETL, with experience developing and optimizing complex data models and pipelines
• Hands-on experience with workflow management tools (e.g., Airflow or similar)
• Proficiency in a scripting language like Python or Bash
• Comfortable working directly with cross-functional teams (data analytics, data science, engineering) to align solutions with business goals

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 $136,000 - CAD $170,000, 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.

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist Intern who can help us discover the value out of our rich and large datasets. Our ideal team member will have the mathematical and statistical expertise you’d expect, but a natural curiosity and creative mind that’s not so easy to find. As you mine, interpret and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. You will join a team of data specialists, but will “slice and dice” data using your own methods, creating new visions for the future. If you love technology and are keen to join an industry leader — we would love to hear from you!

What you'll do:

As a Data Scientist Intern, you will be a crucial part of producing innovative analytics from Geotab’s big data environment. We believe that there is collective value in the massive amount of data arising from all of our sensors across the globe. And most importantly, we believe this data can be used to improve safety, infrastructure, and productivity for our customers. You will work with our team of data scientists and engineers who have curated our data repository and have created a series of near real-time and historical datasets. You will leverage data mining techniques, Machine Learning, Deep Learning, Neural Networks and other Artificial Intelligence and statistical analysis tools to build models and high-quality prediction systems to help our customers make informed and smarter decisions. You will work closely with Data Analysts, Data Engineers, Professional Services, Data Privacy & Governance, firmware as well as other internal departments such as Software Development and Solutions Engineering to achieve these objectives.

The opportunity:

• 8+ month work-term beginning September 2026.
• Full-time, paid internship: Monday - Friday, 37.5hrs/week.
• Your first week at Geotab begins with 'GEO Launch' - a one-week Employee Orientation. Click here to learn more!
• Learn more about the Geotab Campus Program here.
• This posting is for an existing vacancy.

How you'll make an impact:

• The primary objective of this internship is to develop a "Reasoning & Automation" solution that evolves Geotab Ace into a fully integrated, context-aware assistant. Key goals include:
  • Multi-Modal Ingestion: Implement a multi-modal ingestion layer (leveraging technologies like Google's LiveAPI) capable of processing screen content, audio, and text simultaneously to establish real-time user context.
  • Contextual Enrichment: Develop mechanisms to automatically enrich user prompts with environmental state (e.g., current page URL, visible data charts), eliminating the need for users to manually explain their context.
  • Proactive Assistance & Navigation: Extend the reasoning capabilities of the agent to not only answer data queries but also guide users through complex workflows ("Where do I go to...") and offer proactive support.
  • Optimization of RAG & SQL Generation: Continue to refine the underlying RAG architecture and "text-to-SQL" generation for Google BigQuery to ensure the answers provided are accurate, safe, and efficient.

What you'll bring to the role:

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.

We are a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca, AutoSync, Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence. 

AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond.

What's in it for you:

We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from that support us to be our creative best. 

• Gym discounts 

• Employee and Family Assistance program 

• Virtual wellness events 

• Conferences & training budget 

• Regular internal training programs 

• Financial planning with 3% matching Pension  

• Competitive salary 
• Annual bonus structure 

For a career where you can drive our business and shape your future, apply now. 

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.

Build the ads platform that powers the shop local movement.

Faire connects independent retailers with the world's best brands. Ads is how we accelerate that mission: helping brands reach the right retailers, understand what's working, and grow their business on Faire.

This is a high-visibility, high-impact role on one of Faire's top priorities heading into IPO.

Why now?

The Ads team is expanding from 1 team to 3 in 2026. You're joining early enough to shape the direction of the product, with enough already in place to ship meaningful work from day one.

What you'll do:

This is a full-stack product engineering role. 

• You own projects end to end, across frontend, backend, and data.
• Partner with PMs and designers to define the why and what, not just the how; your product instincts matter here
• Contribute to Faire's server-driven UI framework: set technical direction, ensure scalability, and drive adoption across the team
• Optimize frontend performance using Next.js and modern web techniques
• Use AI tooling as a genuine part of your workflow, not as an experiment
• Raise the bar for the engineers around you through code review, pairing, and sharing what you know

What we're looking for:

Must-haves:

• 5+ years of full-time engineering experience (we look at the whole picture)
• Strong frontend depth in TypeScript and React; you can own a complex fullstack project top to bottom
• Product-driven and customer-centric; you think about our customers, not just the technology.
• Comfortable in high-ambiguity environments; you move fast, communicate clearly, and don't wait for perfect specs
• AI tooling is genuinely part of how you work today; you can speak to what you use, what works, and what doesn't

Preferred:

• Background in ad tech, ads manager tools, or customer-facing analytics
• Experience leading a complex frontend project with multiple stakeholders, or mentoring a small group of frontend engineers
• Hands-on experience with data pipelines (Airflow, Spark, or similar)

Tech we use: TypeScript, React, Next.js, Kotlin, Python, Airflow, Jest, Cypress. Strong fundamentals matter more than a specific stack.

Salary range:

Canada: the pay range for this role is $156,000 - $214,500 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.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold  thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Customer Intelligence and AI (CIAI) team is a specialized Data Science group within Robinhood’s Corporate Strategy organization. Our mission is to unlock deeper insights into customer behaviors, satisfaction, and market performance through Net Promoter Score (NPS), benchmarking, and advanced analytics. We apply data science, machine learning, and AI to improve customer experiences, drive operational efficiency, and inform company-wide strategy.

We partner with teams across Robinhood—including Product, Data, Engineering, Marketing, Finance, and Research. Our work powers strategic decision-making, enhances operational performance, and integrates into data science and AI pipelines across the company.

As a Sr. Analytics Engineer on the CIAI team, you will strengthen and expand Robinhood’s Corporate Strategy and benchmarking capabilities. This includes designing and improving measurement frameworks, conducting deep-dive analyses, and shaping how Robinhood tracks and improves customer experience relative to competitors. You’ll contribute to both recurring programs and new technical projects that advance our ability to measure company performance and improve decision-making efficiently.

This role is based in our Menlo Park, CA office, with in-person attendance expected at least [3] days per week. 

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Partner cross-functionally with product, engineering, and business teams to scope and deliver high-impact analytics initiatives, from metric definitions to fully automated reporting solutions.
• Design and maintain reliable, scalable pipelines and data models using modern data tools (e.g., Airflow, Spark), ensuring performance and accuracy at scale.
• Lead end-to-end development of analytics products—from ingestion to visualization—that meet critically important business, product, and regulatory needs.
  Build internal frameworks and tooling to make high-quality data more accessible and actionable across the organization.
• Support competitive benchmarking efforts, providing technical expertise for competitive intelligence and contextualizing Robinhood’s performance relative to peers.
• Advocate for customers by helping establish best practices in how we measure, interpret, and act on customer feedback.

What you bring

• 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or similar field.
• Strong expertise in advanced SQL, Python scripting, and Apache Spark (PySpark, Spark SQL) for data processing and transformation.
• Proficiency in building, maintaining, and optimizing ETL pipelines, using modern tools like Airflow or similar.
• Experience in building polished and performant dashboards using tools like Superset, Looker, Tableau.
• Strong familiarity with version control (GitHub), CI/CD, and modern development workflows.
• A strong business acumen around business strategy and competitive landscape.
• Ability to work in a fast-paced, and highly multi-functional environment.

What we offer

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
• Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
• Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

About the team + role 

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Data Engineering team builds and maintains the foundational datasets that power decision-making across Robinhood. We design reliable, scalable data systems that support product analytics, growth strategy, financial reporting, experimentation, and machine learning. The team partners closely with Product, Engineering, Data Science, and Finance to ensure accurate, well-modeled data is available to teams across the company. Our work directly influences how Robinhood measures performance, improves customer experience, and scales its products.

As a Senior Data Engineer, you will design, build, and evolve core datasets that track product performance and company-wide metrics. You will develop scalable data pipelines that ingest application events and database snapshots into our data lake, ensuring high data quality and reliability. You’ll collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This is an opportunity to shape the technical foundation that supports data-informed decisions across the organization!

This role is based in our Menlo Park, CA office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Help define and build key datasets across all Robinhood product areas. Lead the evolution of these datasets as use cases grow.
• Build scalable data pipelines using Python, Spark and Airflow to move data from different applications into our data lake.
• Partner with upstream engineering teams to enhance data generation patterns.
• Partner with data consumers across Robinhood to understand consumption patterns and design intuitive data models.
• Ideate and contribute to shared data engineering tooling and standards.
• Define and promote data engineering best practices across the company.

What you bring

• 5+ years of professional experience building end-to-end data pipelines
• Hands-on software engineering experience, with the ability to write production-level code in Python for user-facing applications, services, or systems (not just data scripting or automation).
• Expert at building and maintaining large-scale data pipelines using open source frameworks (Spark, Flink, etc)
• Strong SQL (Presto, Spark SQL, etc) skills.
• Experience solving problems across the data stack (Data Infrastructure, Analytics and Visualization platforms)
• Expert collaborator with the ability to democratize data through actionable insights and solutions.

What we offer

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
• Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
• Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are focused on delivering meaningful results. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

Robinhood’s Analytics Engineering team, part of the Data Science organization, builds the data foundation that supports decision-making across the company. The team develops data products that support product development, regulatory requirements, and business operations. You will work closely with product managers, engineers, and data scientists to transform raw data into reliable, usable datasets.

As an Analytics Engineer, you will design and build ETL pipelines, data models, and analytics tools that support key business decisions. You will contribute to defining metrics, improving dataset quality, and establishing standards for analytics development. This role offers the opportunity to influence how teams access and use data across Robinhood while supporting systems that operate at scale!

This role is based in our Toronto, ON office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What you’ll do

• Work with product, engineering, and data science teams to define metrics and deliver analytics solutions, from data ingestion to reporting
• Design and maintain scalable ETL pipelines and data models using tools such as Airflow and Spark
• Build analytics products that support business, product, and regulatory reporting needs
• Develop internal tools and frameworks to improve data accessibility and usability across teams
• Partner with data scientists to turn raw data into insights that inform product and business decisions
• Promote consistent analytics practices and support teams in using data effectively

What you bring 

• You have 3+ years of experience in analytics engineering, data engineering, data science, or a related field
• You have strong experience with SQL, Python, and Apache Spark for data processing
• You have experience building and maintaining ETL pipelines using tools such as Airflow or similar
• You have experience creating dashboards using tools such as Superset, Looker, or Tableau
• You are familiar with version control systems like Git and modern development workflows
• You can work effectively with partners across engineering, product, and data teams

What we offer

• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, and equity ownership
• Top tier benefits to fuel your work, including supplemental health insurance, ancillary insurance, and mental health support programs
• Lifestyle wallet - a highly flexible employer-paid benefits spending account expenses beyond traditional benefits such as wellness, childcare, learning, and more.
• Time off to recharge including company holidays, paid time off, sick time, paid volunteer time off, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.
• Monthly commuter stipend to help offset in-office commuting costs

Our team is committed to providing an inclusive and welcoming interview experience for all candidates. If you require a specific accommodation during the application or interview process due to a physical or mental condition, please complete this Applicant Accommodation Form to notify our team. The form should only be completed if you need a specific accommodation.

AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process. These tools enhance the efficiency and consistency of our hiring process; however, all hiring decisions are made by our hiring teams.

Vacancy Notice: This job posting represents an existing vacancy that we are actively seeking to fill.

We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca, AutoSync, Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence. 

AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits.Through AutoSync, we provide software solutions to 3,500+ dealers, streamlining their operations, marketing,and sales. Dealertrack Canada is the country’s top automotive financing portal, processing more than 6.5 million credit applications each year. Collateral Management(CMS) is anational tech solution that boosts lien and registration services,recovery services, and insolvency management solutions for Canadian Lenders. 

Learn more at tradercorporation.com. 

ABOUT THE ROLE 

 
As a Senior Analytics Engineer, you will own and shape the analytical data architecture and modelling that powers enterprise reporting, self-service analytics, and AI-driven insights. You will define modeling standards, semantic layers, and data foundations across the organisation and act as a technical leader for reporting, analytics and AI use cases. You will work closely with data platform, data governance, and analytics teams across a modern cloud data stack. This position is permanent and based in Toronto, Canada. 

WHAT YOU’LL DO 

• define and evolve enterprise analytical data models and architecture using AWS technology  

• build and own semantic layers to align KPIs and business logic 

• lead AI-driven analytics use cases such as text-to-SQL and conversational BI 

• Set modeling standards, documentation, and best practices across teams 

• Collaborate with data platform engineering , data governance and the business stakeholders on scalable pipelines 

• Contribute to data modeling best practices  

YOU COME WITH 

• 7+ years in analytics engineering or data engineering roles 

• Advanced SQL skills and strong experience with data modeling 

• Strong experience with AWS, Glue, Athena, S3, and cloud analytics 

• Knowledge of orchestration tools (Airflow, Prefect, Dagster) 

• strong Python and PySpark skills for large-scale data processing 

• experience with AI-driven analytics and semantic modeling 

WHY TRADER 

We support your growth, well-being, and long-term success. Our benefits are designed to help you perform at your best - both at work and in your personal life. Benefits from Day One:  

• Gym membership discounts 

• Employee and Family Assistance Program 

• Virtual wellness sessions 

• Budget for conferences and external training 

• Regular internal learning programs 

• Financial Well-Being 

• 3% employer pension matching 

• Comprehensive income-protection options 

• Compensation 

• Competitive base salary 

• Annual performance bonus 
• 3% CPP matching 

The base salary range for this position is CAD $90k- $140k

This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role the total rewards package may also include benefits, bonus, and other employee offerings.

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. 

WHAT YOU'LL DO

Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:

• Design ML use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
• Build and own the full ML pipeline —  taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
• Drive customer success by providing ongoing technical guidance that ensures data science performance, successful adoption, and measurable outcomes
• Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
• Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
• Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

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$125,000 - CA$188,000/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.

#LI-Hybrid

As Manager of Data Infrastructure, reporting to the Director of Data Engineering, you will lead 5-6 engineers operating critical data platforms that power our AI and analytics strategy. This newly created hands-on leadership role combines technical depth with people management, requiring you to mentor your team, drive agile delivery, and apply product thinking to infrastructure. You'll execute on our data strategy while ensuring operational excellence for platforms processing billions in monthly transaction data.

We work Flexible First. This role can be performed remotely anywhere within the provinces of Ontario and British Columbia, Canada. Quarterly travel to the United States is required. We’d love for you to join us!

The Impact You'll Have

• Lead 5-6 engineers through hands-on technical mentoring, performance management, and career development while fostering operational excellence.
• Own data lake infrastructure operations (S3, Airflow, Kafka/MSK, Spark/Glue) maintaining 99.5% uptime and managing on-call rotation.
• Drive agile delivery with sprint planning, capacity planning, and requirements analysis to ship infrastructure improvements quarterly.
• Apply product thinking by gathering customer requirements from data teams, prioritizing platform features, and measuring adoption success.
• Execute technical roadmaps that deliver on data strategy, translating vision into concrete project plans with measurable outcomes.
• Partner with security/compliance on governance controls and work with vendors on technical integrations and platform optimization.

Who You Are

• 6+ years in data engineering/infrastructure with 2+ years leading technical teams at scale.
• Deep hands-on expertise with AWS data services (S3, EMR/Glue), Airflow, Kafka/MSK, and data catalog tools.
• Strong product thinking with experience translating customer requirements into platform capabilities.
• Proven agile delivery skills including capacity planning, sprint execution, and requirements analysis.
• Track record of operational excellence: on-call management, incident response, and achieving SLAs.
• Excellent mentoring skills with passion for developing engineers and building high-performing teams.
• Must be authorized to work in Canada with ability to travel quarterly to the United States.

Nice-To-Haves

• Experience with payments or the FinTech space.

Typical Process

• Application Submission
• Recruiter video call
• Hiring manager video call
• Virtual “Onsite” consisting of four 45-60 min video calls
• Offer!

This position is for an existing vacancy.

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD,  is: 156,800 - 196,000.

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

As Manager of Data Infrastructure, reporting to the Director of Data Engineering, you will lead 5-6 engineers operating critical data platforms that power our AI and analytics strategy. This newly created hands-on leadership role combines technical depth with people management, requiring you to mentor your team, drive agile delivery, and apply product thinking to infrastructure. You'll execute on our data strategy while ensuring operational excellence for platforms processing billions in monthly transaction data.

We work Flexible First. This role can be performed remotely anywhere within the provinces of Ontario and British Columbia, Canada. Quarterly travel to the United States is required. We’d love for you to join us!

The Impact You'll Have

• Lead 5-6 engineers through hands-on technical mentoring, performance management, and career development while fostering operational excellence.
• Own data lake infrastructure operations (S3, Airflow, Kafka/MSK, Spark/Glue) maintaining 99.5% uptime and managing on-call rotation.
• Drive agile delivery with sprint planning, capacity planning, and requirements analysis to ship infrastructure improvements quarterly.
• Apply product thinking by gathering customer requirements from data teams, prioritizing platform features, and measuring adoption success.
• Execute technical roadmaps that deliver on data strategy, translating vision into concrete project plans with measurable outcomes.
• Partner with security/compliance on governance controls and work with vendors on technical integrations and platform optimization.

Who You Are

• 6+ years in data engineering/infrastructure with 2+ years leading technical teams at scale.
• Deep hands-on expertise with AWS data services (S3, EMR/Glue), Airflow, Kafka/MSK, and data catalog tools.
• Strong product thinking with experience translating customer requirements into platform capabilities.
• Proven agile delivery skills including capacity planning, sprint execution, and requirements analysis.
• Track record of operational excellence: on-call management, incident response, and achieving SLAs.
• Excellent mentoring skills with passion for developing engineers and building high-performing teams.
• Must be authorized to work in Canada with ability to travel quarterly to the United States.

Nice-To-Haves

• Experience with payments or the FinTech space.

Typical Process

• Application Submission
• Recruiter video call
• Hiring manager video call
• Virtual “Onsite” consisting of four 45-60 min video calls
• Offer!

This position is for an existing vacancy.

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. 

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position, reflected in CAD,  is: 156,800 - 196,000.

We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.

Along with monetary compensation, Marqeta offers

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company 
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development
• Family-forming benefits and up to 20 weeks of Parental Leave

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

Job Summary: 

We are seeking a highly skilled and self-motivated Senior Embedded DevOps Engineer to support our engineering  teams. This role will focus on driving changes and ensuring adherence to company-established standards for data infrastructure and CI/CD pipelines. The ideal candidate will have strong experience working with AWS and/or GCP,  cloud-based data streaming and processing services, containerized application deployments, infrastructure automation, and Site Reliability Engineering (SRE) best practices for performance and cost optimization.

What You'll do:

• Drive initiatives to implement and enforce best practices for data streaming, processing, analytics and monitoring infrastructure.
• Deploy and manage services on Kubernetes-based platforms such as Amazon EKS and Google Kubernetes Engine (GKE).
• Provision and manage cloud infrastructure using Terraform, ensuring best practices in security, scalability, and cost-efficiency.
• Maintain and optimize CI/CD pipelines using Jenkins, ArgoCD, and GitHub Enterprise Actions to support automated deployments and testing.
• Work with cloud-native data services such as AWS Kinesis, AWS Glue, Google Dataflow, and Google Pub/Sub, BigQuery, BigTable
• Familiarity with  workflow orchestration services such as Apache Airflow and Google Cloud Composer.
• Develop and maintain automation scripts and tooling using Python to support DevOps processes.
• Monitor system performance, troubleshoot issues, and implement proactive solutions to enhance reliability and efficiency.
• Implement SRE practices to improve service reliability, scalability, and cost-effectiveness.
• Analyze and optimize cloud costs, identifying areas for improvement and implementing cost-saving strategies.
• Ensure compliance with security policies and best practices in cloud environments.
• Drive adoption of company standards and influence data teams to align with best DevOps and SRE practices.
• Collaborate with cross-functional teams to improve development workflows and infrastructure.

What you bring:

• 7+ years of experience in a DevOps, Site Reliability Engineering, or Cloud Infrastructure role.
• Strong experience with AWS and GCP data services, including Kinesis, Glue, Pub/Sub, and Dataflow.
• Proficiency in deploying and managing workloads on Kubernetes (EKS/GKE) in production environments.
• Hands-on experience with Infrastructure-as-Code (IaC) using Terraform.
• Expertise in CI/CD pipeline management using Jenkins, ArgoCD, and GitHub Enterprise Actions.
• Programming skills in Python for automation and scripting.
• Experience with observability and monitoring tools (e.g., Prometheus, Grafana, Datadog, or CloudWatch).
• Strong understanding of SRE principles, including performance monitoring, incident response, and reliability engineering.
• Experience with cost optimization strategies for cloud infrastructure.
• Self-motivated and driven, with a strong ability to influence and drive changes across multiple teams.
• Ability to work collaboratively in an agile environment and support multiple teams. 

Preffered Qualifications:

• Experience with data lake architectures and big data processing frameworks (e.g., Apache Spark, Flink, Snowflake, BigQuery).
• Familiarity with event-driven architectures and message queues (e.g., Kafka, RabbitMQ).
• Experience with workflow orchestration tools such as Apache Airflow and Google Cloud Composer.
• Knowledge of service mesh technologies like Istio.
• Experience with GitOps workflows and Kubernetes-native tooling.

#LI-SK1

#LI-Hybrid

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.

Data Scientist, Pricing

Location: In office 4 days a week; Ontario, Canada.

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.

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

#LI-KC1

Data Scientist, Pricing

Location: Hyrbrid 4 onsite, 1 remote Seattle WA. 

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.

Base salary range for this role varies. Generally, the base salary range is $186,000 – $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).

#LI-RO

#

#LI-KC1

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

The role

Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!

You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.

To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally. 

What you’ll do

• Join and become an integral part of a high-impact team covering menu personalization.
• Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
• Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
• Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
• Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
• Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
• Analyze the performance of our models to understand customer behavior, and come up with improvements.
• Contribute to a collaborative and knowledge-sharing environment.

What you’ll bring

• Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
• Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
• In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
• Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
• Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
• Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
• You love to learn, are a critical thinker and creative problem solver who strives for excellence.
• You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.
• Exceptional communication and collaboration capabilities.
• Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.

Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.

Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

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.

#DATA

At Rockstar Games, we create world-class entertainment experiences. 

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. 

Rockstar is on the lookout for a talented Technical Artist who possess a passion for technology and innovation. 

This is a full-time, in-office position based out of Rockstar’s new state-of-the-art game development studio in Carlsbad, CA

WHAT WE DO

• The Rockstar Games Technical Art team creates, maintains and enhances tools and workflows for artists across our Art, Animation, and VFX teams.  
• We create and maintain photogrammetry tools and pipelines, and support live scan sessions.  
• We drive innovation and efficiency in our pipelines by continuously researching and developing new technology.  

RESPONSIBILITIES

• Design, develop, and support tools and pipelines in DCC and standalone contexts.  
• Develop automated solutions for data processing.   
• Stay informed on the latest technology and research related to the art of data pipelines and machine learning.  
• Write clear and detailed documentation for tools and workflows. 
• Diagnose and solve technical issues affecting artists.  

REQUIREMENTS

• 5+ years of experience as a Technical Artist, Technical Director, Tools Programmer, or similar.  
• Experience developing tools for DCCs like Houdini, Zbrush, Agisoft, or Metashape. 
• Experience working through a full game production cycle or long-term project. 
• A strong understanding of Photogrammetry workflows and software.  
• Proficiency in Python. 
• Experience with build systems like Jenkins, Airflow, or Celery.   
• An understanding of a 3D asset pipeline and color management.   
• Ability to think creatively and develop innovative solutions to complex problems. 

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• A degree in Computer Science or related discipline.  
• C++ programming skills.  
• Experience working with package management and deployment systems like Rez or PyPi.  
• Experience with ML based photogrammetry workflows like Gaussian Splats or Nerfs.

HOW TO APPLY

Please apply with a resume and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect.  In line with this commitment, Rockstar will provide accommodations to job applicants with disabilities (or on the basis of any other protected ground under human rights legislation) during the recruitment process, as well as to any Rockstar employees in order for them to perform the essential functions of their roles.  Rockstar will comply with its obligations under the Human Rights Code and the Accessibility for Ontarians with Disabilities Act and will provide accommodations as long as such accommodations do not pose an undue hardship on Rockstar.  If you need more information about Rockstar’s accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.  

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

#LI-AS1

WHAT YOU'LL DO

Join the AI Platform team at Braze to build and scale BrazeAI Decisioning Studio - a reinforcement learning platform at the forefront of AI Decisioning. The platform runs continuous experimentation and personalizes customer engagement at the individual level, helping brands move from rule-based campaigns to autonomous, self-optimizing interactions. You'll work at the intersection of cloud-native infrastructure, data-intensive systems, and machine learning in production.

Main responsibilities:

• Build and maintain critical services and subsystems on our AI platform, balancing performance with cost-effective operations
• Implement cloud-native solutions that ensure reliability, scalability, and fault tolerance
• Troubleshoot production incidents end-to-end, going deep to identify root causes and implement durable fixes
• Contribute to observability practices using Sentry and Datadog to proactively detect issues and minimize downtime
• Collaborate with data scientists, ML engineers, and product teams to translate real-world use cases into platform capabilities
• Improve developer experience by streamlining workflows, enhancing tooling, and supporting MLOps best practices

Tech stack:

• Core Data & ML: Python, Ibis, FastAPI, Dataproc (Spark), SQL, BigQuery, MLflow, Streamlit
• Platform & Infrastructure: Google Cloud Platform, AWS, Kubernetes, Helm, Terraform
• Workflows & Orchestration: Airflow, RabbitMQ, Celery
• CI/CD: GitHub Actions, Jenkins
• Observability: Sentry, Datadog

Why this role:

• Production ML at scale: no toy datasets or notebook demos; you’re building infrastructure that powers real AI workloads
• Engineering rigor: unit and integration tests, modular design, CI/CD, pair programming, and code reviews are how we work, not aspirations
• Learn continuously: deep exposure to ML system architecture, end-to-end ML workflows, and reinforcement learning systems

WHO YOU ARE

• 2-4 years of experience in platform engineering, infrastructure, or a related backend role
• Solid understanding of platform architecture, particularly in ML or data-intensive environments
• Hands-on experience with Kubernetes and cloud infrastructure (GCP preferred)
• Ability to troubleshoot complex distributed systems under pressure
• Writes clean, modular code with a focus on testable APIs and maintainable design
• Experience working with AI coding assistants. Understands effective prompting strategies and can articulate when these tools add value versus when they're not appropriate
• Clear communicator who can work across technical and non-technical stakeholders
• Proactive problem solver who identifies issues and works around obstacles without waiting for direction

For candidates based in Ontario, the pay range for this position at the start of employment is expected to be between CA$125,280 and CA$235,736/year with an expected On Target Earnings (OTE) between CA$139,200 and CA$258,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized 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.

As a Senior Engineer on the Data Platform team at Movable Ink, you will help design and build the systems that power how data flows through the organization. You will play a key role in developing and operating the unified data platform responsible for ingesting, processing, and exposing large volumes of data that drive Movable Ink’s products. Working closely with teammates across engineering, analytics, and infrastructure, you will build scalable ingestion pipelines and backend services that integrate data from a variety of sources while ensuring reliability, governance, and high availability across the platform. You will help evolve legacy pipelines toward modern data architectures, and help drive the unification of our products and services in how they access data. Your work will directly impact the growth and maturity of Movable Ink’s products and services.

Responsibilities:

• Support the design and delivery of data ingestion pipeline and infrastructure
• Assist in the successful migration of legacy data lifecycle management to new platform without disrupting existing data consumers
• Establish and maintain SLIs and SLOs for new ingestion and data platform with dashboards and alerting to track performance
• Build flexible data storage layer supporting a variety of use cases, e.g., transactional, analytic, and machine learning workloads
• Implement comprehensive monitoring, observability, and incident response practices for all event data pipelines and services
• Collaborate with product engineering, analytics, and machine learning teams to define contracts, functional requirements, and standards
• Design and implement a semantic metadata layer that classifies and labels data assets across both products, enabling consistent data discovery, exposure policies, and identification of cross-product data reuse opportunities
• Architect and deliver a multi-tenant data model that supports secure data sharing and isolation across clients, with controls designed to meet regulatory and government compliance requirements

Qualifications:

• Deep understanding of data governance principles and data lifecycle management, including data quality, lineage, retention, and access control
• Strong familiarity with database backend technologies (OLAP vs. OLTP) and when to apply each, with hands-on experience using data warehouse technologies (Databricks, Clickhouse, Redshift, etc) at production scale
• Strong familiarity with SQL with the ability to write and optimize queries
• Skill at building complex systems and identifying core primitives and how to apply them to meet changing business needs and future roadmap requirements.
• Experience designing and operating data systems on a major cloud provider (AWS or GCP) and working in a multi-cloud deployment environment
• Proficiency with containerization and orchestration technologies, including Docker and Kubernetes
• Proven ability to integrate systems, connecting legacy platforms with modern architectures through well-designed interfaces and migration strategies
• Effective communicator who can facilitate system design discussions, document architectural decisions, and work across team boundaries
• (Nice to have) Familiarity with Elixir for building concurrent, fault-tolerant data services
• (Nice to have) Experience with data pipeline and streaming technologies such as Airflow, Kafka, Apache Flink, or similar
• (Nice to have) Hands-on experience with columnar/OLAP databases such as Databricks or ClickHouse
• Experience designing and operating data systems on AWS; GCP experience is a plus
• Strong collaboration and communication skills, comfortable leading design discussions, writing technical specs, and working across team boundaries
• Experience with Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or similar

The base pay range for this position is $145,000-$185,000/year, which can include additional bonus depending on the position ultimately offered, in addition to a full range of medical, financial, and/or other benefits. The base pay offered may vary depending on job-related knowledge, skills, and experience.

What You'll Be Doing:

• Design and build scalable data pipelines, batch jobs, and streaming processes that power analytics and machine learning.
• Implement and optimize data storage systems (warehouses, lakes, analytical databases) with a focus on reliability, lineage, and governance.
• Develop tools and frameworks to support data orchestration, ETL workflows, and big data processing.
• Collaborate with engineers, data scientists, and product managers to align platform capabilities with business needs.
• Ensure data systems meet requirements for quality, scalability, and cost efficiency in cloud environments.
• Contribute to technical discussions, code reviews, and system design sessions.
• Take ownership of features and projects, driving them from concept to production.

At Rockstar Games, we create world-class entertainment experiences. 

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. 

Rockstar is on the lookout for a talented Technical Artist who possess a passion for technology and innovation. 

This is a full-time, in-office position based out of Rockstar’s unique game development studio in Oakville, ON. 

WHAT WE DO

• The Rockstar Games Technical Art team creates, maintains and enhances tools and workflows for artists across our Art, Animation, and VFX teams.  
• We create and maintain photogrammetry tools and pipelines, and support live scan sessions.  
• We drive innovation and efficiency in our pipelines by continuously researching and developing new technology.  

RESPONSIBILITIES

• Design, develop, and support tools and pipelines in DCC and standalone contexts.  
• Develop automated solutions for data processing.   
• Stay informed on the latest technology and research related to the art of data pipelines and machine learning.  
• Write clear and detailed documentation for tools and workflows. 
• Diagnose and solve technical issues affecting artists.  

REQUIREMENTS

• 5+ years of experience as a Technical Artist, Technical Director, Tools Programmer, or similar.  
• Experience developing tools for DCCs like Houdini, Zbrush, Agisoft, or Metashape. 
• Experience working through a full game production cycle or long-term project. 
• A strong understanding of Photogrammetry workflows and software.  
• Proficiency in Python. 
• Experience with build systems like Jenkins, Airflow, or Celery.   
• An understanding of a 3D asset pipeline and color management.   
• Ability to think creatively and develop innovative solutions to complex problems. 

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• A degree in Computer Science or related discipline.  
• C++ programming skills.  
• Experience working with package management and deployment systems like Rez or PyPi.  
• Experience with ML based photogrammetry workflows like Gaussian Splats or Nerfs.

HOW TO APPLY

Please apply with a resume and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect.  In line with this commitment, Rockstar will provide accommodations to job applicants with disabilities (or on the basis of any other protected ground under human rights legislation) during the recruitment process, as well as to any Rockstar employees in order for them to perform the essential functions of their roles.  Rockstar will comply with its obligations under the Human Rights Code and the Accessibility for Ontarians with Disabilities Act and will provide accommodations as long as such accommodations do not pose an undue hardship on Rockstar.  If you need more information about Rockstar’s accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.  

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

#LI-AS1

At Rockstar Games, we create world-class entertainment experiences. 

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. 

Rockstar is on the lookout for a talented Technical Artist who possess a passion for technology and innovation. 

This is a full-time, permanent and in-office position based out of Rockstar’s unique game development studio in the heart of Leeds, England. 

WHAT WE DO

• The Rockstar Games Technical Art team creates, maintains and enhances tools and workflows for artists across our Art, Animation, and VFX teams.  
• We create and maintain photogrammetry tools and pipelines, and support live scan sessions.  
• We drive innovation and efficiency in our pipelines by continuously researching and developing new technology.  

RESPONSIBILITIES

• Design, develop, and support tools and pipelines in DCC and standalone contexts.  
• Develop automated solutions for data processing.   
• Stay informed on the latest technology and research related to the art of data pipelines and machine learning.  
• Write clear and detailed documentation for tools and workflows. 
• Diagnose and solve technical issues affecting artists.  

REQUIREMENTS

• 5+ years of experience as a Technical Artist, Technical Director, Tools Programmer, or similar.  
• Experience developing tools for DCCs like Houdini, Zbrush, Agisoft, or Metashape. 
• Experience working through a full game production cycle or long-term project. 
• A strong understanding of Photogrammetry workflows and software.  
• Proficiency in Python. 
• Experience with build systems like Jenkins, Airflow, or Celery.   
• An understanding of a 3D asset pipeline and color management.   
• Ability to think creatively and develop innovative solutions to complex problems. 

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• A degree in Computer Science or related discipline.  
• C++ programming skills.  
• Experience working with package management and deployment systems like Rez or PyPi.  
• Experience with ML based photogrammetry workflows like Gaussian Splats or Nerfs.

HOW TO APPLY

Please apply with a resume and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect.  In line with this commitment, Rockstar will provide accommodations to job applicants with disabilities (or on the basis of any other protected ground under human rights legislation) during the recruitment process, as well as to any Rockstar employees in order for them to perform the essential functions of their roles.  Rockstar will comply with its obligations under the Human Rights Code and the Accessibility for Ontarians with Disabilities Act and will provide accommodations as long as such accommodations do not pose an undue hardship on Rockstar.  If you need more information about Rockstar’s accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.  

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

#LI-AS1

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

The Role

As a Technical Delivery Project Manager, you support the successful execution of internal technical workstreams required for customer delivery. You serve as the day-to-day liaison between internal technical teams (e.g., Data Engineering, Data Science, Integrations, R&D) and the customer-facing delivery team. You coordinate technical requirements, gather inputs from customers, help translate requirements into internal technical tasks, manage supporting documentation, and ensure technical deliverables are completed on time.

In this role, you work closely with the Delivery Lead and functional technical leads to ensure alignment, visibility, and smooth execution of technical dependencies. You apply strong working knowledge of tools like Jira and foundational technical literacy to understand and communicate risks, issues, and timelines. You operate with growing independence while receiving guidance for complex or ambiguous matters.

One specific area of responsibility is to manage League’s customer-facing data product called Analytics Objects (AOs), which is a recurring data export of complex KPIs configured to meet a wide range of customer requirements. Your responsibilities include:

In this role, you are expected to:

Technical Workstream Coordination

• Coordinate technical tasks and dependencies across Data, Engineering, R&D, and other internal technical teams.
• Translate customer requirements into clear Jira tickets or internal work items.
• Maintain visibility into task progress, blockers, and timelines.

Manage Data Products 

• Coordinate launch of Analytics Objects (AOs) and other data products to customers.
• Manage the configuration of AOs and other data products to suit customer use cases.
• Manage customization requests and recommend existing solutions to customers as needed. Coordinate with product managers on custom solutions.

Customer Engagement & Requirements Gathering

• Attend customer-facing technical requirement meetings as a supporting point of contact.
• Document technical requirements and ensure internal technical teams understand expected outcomes.
• Communicate updates, risks, and next steps back to customer-facing stakeholders.

Jira & Tooling Ownership

• Support maintaining Jira boards, grooming tasks, updating statuses, and ensuring accurate workflow progression for tasks related to customer delivery.
• Support reporting on technical delivery progress and timelines.

Risk & Issue Management

• Identify and flag risks or blockers related to technical workstreams.
• Escalate issues to the Delivery Lead or technical leads as needed.

Technical Delivery Support

• Support internal test cycles, data validation activities, and technical documentation requirements.
• Understand and articulate the impact of deviations from standard practices.

Process & Documentation

• Maintain technical requirement documentation, task tracking, and workstream-level artifacts.
• Contribute feedback to help improve technical delivery processes and tooling.

About You:

• 3+ years in SaaS technical coordination, technical support, or data operations.
• Working knowledge of data platforms (Airflow, BigQuery, Looker, or similar).
• Strong proficiency with Jira for workflow tracking and ticket management.
• Foundational understanding of SaaS architectures, APIs, data pipelines, or ETL.
• Experience collaborating with Data teams, R&D, or technical SMEs.
• Experience managing projects with complex technical dependencies.

What We Offer

• Comprehensive Health Benefits: We prioritize your well-being with complete medical, dental, and vision coverage
• Bonus Program: Be rewarded for your contributions with our performance-based bonus program
• Employee Stock Option Program: Become an owner and share in our success through our stock option program
• Unlimited Paid Time Off: Take the time you need to recharge and maintain a healthy work-life balance
• Spending Accounts: Manage your healthcare and dependent care expenses with tax-advantaged spending accounts
• Wellness Days: Prioritize your mental and physical health with dedicated wellness days throughout the year
• Growth Opportunities: We invest in your future with abundant opportunities for professional development and advancement
• Mentorship Program: Benefit from guidance and support from experienced leaders in your field

Security-related Responsibilities

• Compliance with Information Security Policies
• Compliance with League’s secure coding practice
• Responsibility and accountability for executing League's policies and procedures
• Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations

Please note: We’re always excited to connect with exceptional talent. This posting is part of our proactive talent community efforts. While there may not be an immediate opening, we review applications on an ongoing basis and reach out as opportunities arise.

• Use AI tools as part of your daily workflow to enhance productivity, problem-solving, and decision-making (e.g., drafting, analysis, coding, research, or process automation)
• Apply judgment and accountability when using AI by reviewing outputs for accuracy, bias, and quality before use
• Continuously learn and adapt as new AI tools and capabilities emerge, incorporating them into your ways of working
• Identify opportunities to improve how work gets done from personal productivity to team-level workflows by leveraging AI effectively
• Operate with strong data responsibility and security awareness, especially when working with sensitive or regulated information

• Individual Contributors: Use AI to improve personal productivity and quality of output
• Senior ICs / Managers: Integrate AI into team workflows and improve processes
• Leaders: Drive AI adoption at the organizational level and shape how work is done across teams

• Demonstrated experience using AI tools in a practical, responsible way
• Curiosity and openness to experimenting with new technologies
• Ability to balance efficiency with quality and sound judgment

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

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.

This role is for a highly experienced technical leader in the data space, whose influence spans multiple Platform and Product groups.

Within the Platform group:

• The Data Infrastructure team builds and operates a secure, reliable, cost-efficient, opinionated platform for data ingestion, storage, compute, orchestration, and governance. 
• The Analytics Platform team builds efficient data warehousing capabilities, foundational data assets, and tools to accelerate data-driven analytics. Its mandate is to reduce time from data to insights.

The teams also own relationships with relevant technology infrastructure vendors.

Additionally, this role would influence and interact with all data and analytics related functions at Faire. The product analytics engineering (PAE) function enables domain-specific AE capabilities, working closely with Data Science, Strategy & Analytics, Finance. The data science (DS) function leads modeling development and evaluation, raising effectiveness and efficiency of key product features.

We’re looking for: An experienced technical leader with data and analytics background to work alongside and lead / influence across multiple teams and departments. Define technology strategy, roadmaps, architecture patterns and guidance. Striking the right balance of technical leadership and hands-on development.

What you’ll do

• Plan and execute on technology projects that scale with Faire’s growth; lead architecture development with a focus on data integrity, security, performance, scale, reliability, monitoring/alerting.
• Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals.
• Provide technical guidance and mentorship on the most difficult open-ended problems we face. Including cost-efficient compute and storage, ETL and ELT pipelines, data ingest and warehousing, monitoring, alerting, and cost tracking for workloads, design practices for foundational assets, data security, privacy, and governance.

Qualifications

• Experience designing, developing, and operating data streaming, batch, ETL/ELT, orchestration, storage, compute, workflow systems at scale.
• Experience defining architecture patterns and building reliable, scalable data pipelines, orchestration of data movement, querying, transformation, and frameworks for analytics engineering workflows.
• Strong SQL and Python skills and experience.
• Data warehousing experience at Petabyte scale.
• Snowflake, Airflow, Spark experience especially valuable.
• Understanding of performance, capacity, cost trade-offs in data processing systems. Experience in guiding technical and product teams on such trade-offs.
• Experience diagnosing, mitigating, and permanently addressing data system production issues at scale. Experience rolling out patterns for workload performance and cost optimization.
• Experience operating in a growth stage company, with a data function consisting of multiple teams and over 60 people. Enabling teams to operate in a self-serve model.
• Excellent communication, leadership, and influencing skills.
• A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience.
• Select technologies we use and teach: AWS, Snowflake, Airflow, Spark, Python, Kotlin.

Salary Range

San Francisco: the pay range for this role is $268,000 to $368,500 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 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.

This role is for a highly experienced technical leader in the data space, whose influence spans multiple Platform and Product groups.

Within the Platform group:

• The Data Infrastructure team builds and operates a secure, reliable, cost-efficient, opinionated platform for data ingestion, storage, compute, orchestration, and governance. 
• The Analytics Platform team builds efficient data warehousing capabilities, foundational data assets, and tools to accelerate data-driven analytics. Its mandate is to reduce time from data to insights.

The teams also own relationships with relevant technology infrastructure vendors.

Additionally, this role would influence and interact with all data and analytics related functions at Faire. The product analytics engineering (PAE) function enables domain-specific AE capabilities, working closely with Data Science, Strategy & Analytics, Finance. The data science (DS) function leads modeling development and evaluation, raising effectiveness and efficiency of key product features.

We’re looking for: An experienced technical leader with data and analytics background to work alongside and lead / influence across multiple teams and departments. Define technology strategy, roadmaps, architecture patterns and guidance. Striking the right balance of technical leadership and hands-on development.

What you’ll do

• Plan and execute on technology projects that scale with Faire’s growth; lead architecture development with a focus on data integrity, security, performance, scale, reliability, monitoring/alerting.
• Engage with team planning and prioritization, balancing urgent and near-term needs with long-term goals.
• Provide technical guidance and mentorship on the most difficult open-ended problems we face. Including cost-efficient compute and storage, ETL and ELT pipelines, data ingest and warehousing, monitoring, alerting, and cost tracking for workloads, design practices for foundational assets, data security, privacy, and governance.

Qualifications

• Experience designing, developing, and operating data streaming, batch, ETL/ELT, orchestration, storage, compute, workflow systems at scale.
• Experience defining architecture patterns and building reliable, scalable data pipelines, orchestration of data movement, querying, transformation, and frameworks for analytics engineering workflows.
• Strong SQL and Python skills and experience.
• Data warehousing experience at Petabyte scale.
• Snowflake, Airflow, Spark experience especially valuable.
• Understanding of performance, capacity, cost trade-offs in data processing systems. Experience in guiding technical and product teams on such trade-offs.
• Experience diagnosing, mitigating, and permanently addressing data system production issues at scale. Experience rolling out patterns for workload performance and cost optimization.
• Experience operating in a growth stage company, with a data function consisting of multiple teams and over 60 people. Enabling teams to operate in a self-serve model.
• Excellent communication, leadership, and influencing skills.
• A bachelor's degree in Computer Science/Software Engineering or equivalent industry experience.
• Select technologies we use and teach: AWS, Snowflake, Airflow, Spark, Python, Kotlin.

Salary Range

Canada: the pay range for this role is $228,000 to $313,500 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.