Analytics Engineer

Clutch Technologies Inc.; Toronto; On-site; CAD 80,000 - 110,000; Full time

Job summary

Clutch Technologies Inc., a leading online used car retailer in Canada, is seeking an Analytics Engineer to build and optimize their analytics data stack. The role involves collaboration with various teams to enhance reporting and data quality, offering a competitive salary and generous time off. Ideal candidates will have strong SQL skills and experience with data modeling tools like dbt and Snowflake.

Benefits

Autonomy & ownership

Competitive compensation and equity incentives

Generous time off program

Qualifications

• 4–6 years of experience in analytics engineering or data analytics.
• Strong SQL expertise and experience with large datasets.
• Hands-on experience with dbt in a production environment.

Responsibilities

• Build and optimize analytics data stack including ELT pipelines.
• Collaborate across teams to define key metrics and improve reporting.
• Mentor others on data modeling and tooling.

Skills

SQL

Data modeling

Data analytics

Collaboration

Data quality

Education

Bachelor's degree in a relevant field

Tools

dbt

Snowflake

Airflow

BigQuery

Redshift

Looker

Tableau

Job description

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… and that’s just the beginning.

Named one of Canada’s top growing Companies two years in a row and also 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 a number of world-class investors, including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca .

What You'll Do

• Build, maintain, and optimize our analytics data stack, including ELT pipelines, dimensional models, and semantic layers using tools like dbt, Snowflake, and Airflow.
• Collaborate with teams across Marketing, Product, Operations, and Finance to define key metrics, improve reporting fidelity, and unlock self-serve analytics.
• Own and evolve core data models and pipelines that drive reporting, dashboards, and downstream analysis.
• Apply best practices around 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 and trustworthy data products.
• Contribute to and advocate for Clutch’s internal data documentation and governance practices.
• Mentor others on data modeling, tooling, and process — bringing a scalable, engineering-first mindset 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 comfort working with large-scale, normalized, or dimensional datasets.
• Hands-on experience building data models with dbt in a production environment (CI, testing, documentation).
• Experience working with cloud data warehouses like Snowflake, BigQuery, or Redshift.
• Experience building semantic layers and enabling self-serve BI (Looker, Sigma, Tableau).
• A proactive communicator who can collaborate with business stakeholders and technical teams alike.
• A strong sense of ownership and accountability for data quality, performance, and maintainability.
• Familiarity with using Python and orchestration tools (Airflow, Prefect, Dagster) for data pipelines and transformation 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

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 [e-mail] .

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