SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: CAD 160,000 - 200,000 / annual
Clutch is Canada's largest online used car retailer, delivering a seamless car-buying experience. Founded in 2017 and backed by top-tier investors including Canaan, D1 Capital, and Real Ventures, Clutch has been named one of Canada's Top Growing Companies and recognized on LinkedIn's Top Canadian Startups list.
As a Senior Data Engineer, you will own Clutch's data platform end-to-end, designing and evolving the architecture behind the warehouse, pipelines, and data models with long-term scalability in mind. You'll build reliable, well-tested ELT pipelines that integrate data from applications, operational systems, and third-party tools. Working in partnership with analysts and data scientists, you'll design data models that make trusted, well-structured data easy to find and use across the business.
Key responsibilities include:
- Own the data platform architecture, designing for scalability and reliability
- Build and maintain production ELT pipelines using modern tools
- Design analytics-focused data models in collaboration with stakeholders
- Build data foundations for the company's growing financial services work
- Establish data quality, observability, monitoring, testing, and alerting practices
- Apply DevOps best practices including version control, CI/CD, infrastructure as code, and automated deployments
- Leverage AI as part of your engineering workflow to prototype and accelerate development
- Make thoughtful technical decisions balancing speed, cost, quality, and maintainability
- Establish data standards, documentation, and governance as the platform matures
- Mentor team members and raise the bar for data engineering through design discussions and code reviews
The data team uses Snowflake, dbt, Airflow, Python, and AWS. The broader tech stack includes TypeScript, PostgreSQL, and Express. The company values exceptional engineers over perfect technology matches and is interested in candidates who can learn and evolve the stack.
Requirements:
- 5+ years of experience in data engineering or closely related field
- Proven track record building and operating production data pipelines and platforms that people rely on
- Advanced SQL and strong Python programming skills (TypeScript is a plus)
- Hands-on experience with a modern cloud data warehouse (Snowflake, BigQuery, or Redshift)
- Experience with transformation and orchestration tools such as dbt and Airflow
- Experience with cloud platforms, ideally AWS, and their data services
- Strong data modeling skills, including designing for analytics use cases
- Experience with DevOps and observability tooling (Git, GitHub Actions, Docker, Terraform, Datadog)
- Ability to use AI as a force multiplier for exploration, prototyping, and development acceleration
- Comfort working directly with stakeholders to understand problems and deliver business value
- Clear communication skills and ability to make decisions in ambiguous environments
- Equal focus on business outcomes and technical excellence
Nice to have:
- Experience with streaming or event-driven data (Kafka, Kinesis)
- Experience supporting data science or ML workflows in production
- Background in e-commerce, marketplaces, automotive, or fintech
