Senior Data Engineer

• At Clutch, we believe advances in AI are fundamentally changing how great products are built. Traditional handoffs between product, design, and engineering are giving way to smaller, faster teams where builders can take ideas from concept to production in days instead of months
• As a Senior Data Engineer, you’ll own the data platform that powers decision-making across Clutch, from how we buy and price vehicles, to how customers move through our funnel, to how we deliver and finance cars. The pipelines, models, and infrastructure you build will be the foundation our analysts and data scientists rely on every day, including for our fast-growing financial services work
• Our data engineers don’t just move data, they own outcomes. That means working directly with stakeholders to understand what they need, designing systems that scale with the business, and making sure the data behind every important decision is reliable, well-modeled, and easy to use. If you see a broken pipeline or a question the data can’t answer yet and feel compelled to fix it, you’ll thrive at Clutch
• Own Clutch’s data platform end-to-end, designing and evolving the architecture behind our warehouse, pipelines, and data models with long-term scalability in mind
• Build reliable, well-tested ELT pipelines that bring together data from our applications, operational systems, and third-party tools
• Design data models in partnership with analysts and data scientists so that trusted, well-structured data is easy to find and use across the business
• Build the data foundations for our financial services work, partnering closely with the data scientist focused on that area to support modeling, experimentation, and analytics
• Own data quality and observability, with monitoring, testing, and alerting that catch issues before stakeholders do
• Apply strong DevOps practices to data, including version control, CI/CD, infrastructure as code, and automated deployments
• Use AI as part of your everyday engineering workflow to prototype, accelerate development, and improve code quality
• Make thoughtful technical decisions that balance speed, cost, quality, and maintainability, and continuously evaluate new tools that help the team move faster
• Establish data standards, documentation, and governance practices as our platform matures
• Mentor others and raise the bar for data engineering across the team through design discussions and code reviews

Benefits

• Autonomy & ownership: Create your own path and own your work with some of the most talented and creative people in Canada
• Competitive pay + equity: Enjoy competitive pay from day one, with equity opportunities available for roles that shape our future
• Generous time off: From vacation time to parental leave, we believe that work-life harmony is key to a healthy work environment
• Health, dental & more: Your well-being matters. That’s why we offer medical, dental, and wellness support to you and your loved ones

• Experience with cloud platforms, ideally AWS, and their data services
• Enjoy working directly with stakeholders to understand problems and deliver business value
• Care as much about business outcomes as technical excellence
• Experience with DevOps and observability tooling such as Git, GitHub Actions, Docker, Terraform, and Datadog
• Communicate clearly and are comfortable making decisions in ambiguous environments
• Use AI as a force multiplier to explore ideas, prototype solutions, and accelerate development
• 5+ years of experience in data engineering or a closely related field
• Our data team builds with technologies like Snowflake, dbt, Airflow, Python, and AWS, alongside an application stack of TypeScript, PostgreSQL, and Express. We’re far more interested in exceptional engineers than perfect technology matches. If you’ve built outstanding data platforms in another modern stack and are excited to learn, improve, and help evolve ours, we’d love to talk
• Hands-on experience with a modern cloud data warehouse such as Snowflake, BigQuery, or Redshift
• Strong data modeling skills, including designing for analytics use cases
• Experience with transformation and orchestration tools such as dbt and Airflow
• Advanced SQL and strong programming skills in Python (TypeScript is a plus)
• Have built and operated production data pipelines and platforms that people rely on
• Experience with streaming or event-driven data (e.g., Kafka, Kinesis)
• Experience in e-commerce, marketplaces, automotive, or fintech
• Experience supporting data science or ML workflows in production