dbt Labs created the analytics engineering category — SQL-based transformations, version-controlled, tested, and packaged. dbt Cloud is the SaaS layer. The interview is a hybrid of data engineering and traditional software engineering, with strong emphasis on SQL fluency and developer empathy.
Process
Recruiter screen → 60-minute technical phone (often SQL + DSA hybrid) → onsite virtual: 2 coding (one DSA, one practical), 1 system design, 1 past-project deep dive, 1 behavioral. Cycle: 3–4 weeks.
What they actually ask
- Design dbt Cloud orchestration — schedule, retry, dependency-aware execution of model graphs
- Design a metrics layer that compiles to SQL across multiple warehouses (Snowflake, BigQuery, Redshift)
- SQL: complex window functions, recursive CTEs, query optimization tradeoffs
- Coding: graph problems (DAG traversal mirrors dbt model dependencies)
- Behavioral: collaboration with data analysts, explaining tradeoffs to non-engineers
Levels and comp (2026)
- SE II: $170K–$210K total
- Senior SE: $240K–$310K
- Staff: $340K–$450K
- Principal: $480K–$620K
Prep priorities
- Be fluent in SQL (window functions, CTEs, query plans) — this is non-negotiable
- Have hands-on dbt experience or at minimum read the dbt docs and run through tutorials
- Understand modern data stack: Snowflake, BigQuery, Redshift, Airflow, Fivetran
Frequently Asked Questions
Is dbt Labs fully remote?
Yes. ~600 employees distributed globally. Hubs in Philadelphia, NYC, Sydney are optional.
Do I need to know dbt before interviewing?
Strongly preferred. At minimum, install dbt locally and build a small project — they will ask about it.
What is the engineering culture like?
Async-heavy, writing-focused, collaborative. dbt Labs values craft and clear thinking over heroics.