Clutch is hiring a Senior Data Engineer in Toronto!
Clutch, a Toronto-headquartered online used-car retailer founded in 2017, is hiring a Senior Data Engineer to take end-to-end ownership of the company's data platform. The role sits at the centre of how Clutch buys, prices, delivers, and finances vehicles, and the pipelines, models, and infrastructure you build will underpin daily work for analysts and data scientists — including a growing financial services area. Clutch frames the position around outcomes rather than tickets: you'll work straight with stakeholders to understand what they need, then design systems that hold up as the business scales and keep the data behind key decisions trustworthy and well-modelled. The team works with Snowflake, dbt, Airflow, Python, and AWS alongside a TypeScript, PostgreSQL, and Express application stack, but the posting stresses that strong engineers who have built comparable platforms in other modern stacks are welcome to learn theirs. This is a permanent, full-time, hybrid role based in downtown Toronto, with three days a week expected in office. Compensation is listed between $160,000 and $200,000, with equity incentives, a generous time-off program, and health and dental benefits on top.
Key responsibilities
- Own the data platform end to end, shaping the architecture behind the warehouse, pipelines, and data models for long-term scalability
- Build reliable, well-tested ELT pipelines that consolidate data from applications, operational systems, and third-party tools
- Design data models together with analysts and data scientists so trusted data is easy to discover and use
- Lay the data groundwork for financial services work, partnering with the data scientist focused on that area to support modelling, experimentation, and analytics
- Own data quality and observability through monitoring, testing, and alerting that surface problems before stakeholders notice
- Apply DevOps practices to data, including version control, CI/CD, infrastructure as code, and automated deployments
- Use AI in day-to-day engineering to prototype, speed up development, and improve code quality
- Make technical decisions that weigh speed, cost, quality, and maintainability, and keep evaluating tools that help the team move faster
- Establish data standards, documentation, and governance as the platform matures
- Mentor colleagues and raise the bar through design discussions and code reviews
Key requirements
- 5+ years in data engineering or a closely related field
- Track record building and operating production data pipelines and platforms that others depend on
- Advanced SQL plus strong Python programming skills; TypeScript is a plus
- Hands-on work with a modern cloud data warehouse such as Snowflake, BigQuery, or Redshift
- Experience with transformation and orchestration tooling such as dbt and Airflow
- Experience with cloud platforms, ideally AWS, and their data services
- Strong data modelling skills, including design for analytics use cases
- Familiarity with DevOps and observability tools such as Git, GitHub Actions, Docker, Terraform, and Datadog
- Comfort using AI as a force multiplier for exploring ideas and accelerating development
- Enjoyment of direct stakeholder work to understand problems and deliver business value
- Clear communication and comfort deciding amid ambiguity
- Care for business outcomes alongside technical excellence
- Seniority: Senior
- Work mode: Hybrid — downtown Toronto, three days per week in office
- Salary: $160,000 - 200,000
- Key skills: SQL, Python, Snowflake, dbt, Airflow, AWS, Data Modeling, ELT Pipelines, Data Quality, Observability, CI/CD, Terraform, Docker, Git, GitHub Actions
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