Own and evolve dbt models across product data and other internal systems, maintain shared dimensions, facts, transformations, and metrics, partner with domain experts to define company metrics, add tests, improve documentation, and collaborate with Engineering on source contracts, data quality, freshness, warehouse performance, and issues upstream.
The cash compensation range for this role is $160K-$200K
Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications. In addition to cash compensation, all employees receive an equity compensation package.
- Own and evolve dbt models across our product data and other internal systems.
- Maintain shared dimensions, facts, transformations, and metrics as source systems and business requirements change.
- Partner with domain experts to define company metrics, reconcile competing definitions, and consolidate duplicated business logic into trusted, reusable models.
- Add tests for uniqueness, completeness, relationships, business rules, and important edge cases. Improve documentation, lineage, and discoverability.
- Partner with Engineering on source contracts, data quality, freshness, warehouse performance, and issues that start upstream.
- Degree in data science, computer science, statistics, or a similar quantitative field
- Nice to have: Experience at a B2B SaaS or developer tools company
- Nice to have: Background working with append-only history, event data, or change data capture
- Nice to have: Hands on experience with data contracts, lineage, observability, or automated data-quality monitoring
- Nice to have: Familiarity with LLM and AI infrastructure data, or a genuine interest in learning it fast
