What It's Like to Work There
Community-driven and analytics-focused. dbt Labs has built one of the strongest communities in data engineering with dbt Community and Coalesce conferences. Philadelphia-based, which gives them a different vibe from Bay Area startups. Values-driven with emphasis on transparency.
Resume Tips for dbt Labs
dbt experience is the obvious differentiator. If you've used dbt in production, built dbt packages, or contributed to the dbt ecosystem, lead with it.
Data transformation and SQL expertise matters. Show you understand data modeling, warehouse optimization, and analytics patterns.
Python is core to dbt's codebase. Strong Python skills are expected.
If you've built developer tools, testing frameworks, or CI/CD systems, that experience translates to dbt Cloud.
Understanding of the modern data stack (Snowflake, BigQuery, Fivetran, Looker) is valuable context.
Hiring Process
Recruiter screen focused on your data engineering or developer tools experience
Technical phone screen with coding and data modeling questions
Virtual onsite with 4 rounds: coding, system design, data ecosystem understanding, and behavioral
They assess how you think about the analytics engineering workflow
Interview Style
Practical interviews that test data engineering knowledge and software engineering skills. They want to see that you understand the analytics engineering workflow and can build tools that data practitioners love.
Top Roles They Hire
Software Engineer
Data Engineer
Analytics Engineer
Product Manager
Developer Advocate
Solutions Architect
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