dbt Jobs

Most RevOps positions expect proficiency in writing dbt models using SQL, implementing data tests for quality assurance, and creating documentation. Advanced roles may require knowledge of dbt packages for marketing attribution, building incremental models for large datasets, and setting up CI/CD workflows. Experience with dbt Cloud or dbt Core deployment is often specified.

Focus on revenue-specific models you've built: customer lifetime value calculations, multi-touch attribution models, pipeline velocity tracking, cohort analysis for retention, and unified customer data models combining CRM, billing, and product data. Emphasize how your dbt work directly impacted revenue forecasting accuracy or sales team productivity.

At smaller companies (under 200 employees), dbt knowledge is often nice-to-have rather than required, as data volumes may not justify the complexity. However, fast-growing startups frequently adopt dbt early to scale their analytics, making it valuable even in smaller organizations. Focus on learning dbt if you're targeting Series B+ companies or data-intensive industries.