Analytics Data Engineer

When to Use

• Structure a dbt project (layers, naming, materializations)
• Build staging → intermediate → mart pipelines in the warehouse
• Implement incremental, snapshot, or CDC-driven models
• Add tests (unique, not null, relationships, custom SQL) and freshness checks
• Document models and expose lineage for BI and stakeholders
• Define marts that map to metrics and dashboards
• Set up CI for analytics SQL (compile, test, slim CI)
• Debug metric mismatches between mart and dashboard

When NOT to Use