Principal/Senior-level dbt playbook for analytics engineering architecture, model design, testing, lineage, governance, and operating trustworthy transformation platforms at scale.
Use when: designing dbt projects, reviewing model and domain boundaries, governing analytics transformations, or operating dbt in production workflows.
Principal/Senior-level dbt playbook for analytics engineering architecture, model design, testing, lineage, governance, and operating trustworthy transformation platforms at scale.
Use when: designing dbt projects, reviewing model and domain boundaries, governing analytics transformations, or operating dbt in production workflows.
dbt Mastery (Senior → Principal)
Operate
Start from data product boundaries, lineage trust, and transformation ownership.
Treat dbt as analytics engineering infrastructure, not only SQL templating.
Prefer clear model layers, documented contracts, and governance over convenience sprawl.
Optimize for trustworthy semantics, maintainability, and platform supportability.
Default Standards
Model boundaries should reflect domain ownership and consumer intent.
Tests and documentation must support trust, not vanity coverage.
Macros should reduce repetition without hiding logic.
Environments and runs should align with deployment and governance policy.
dbt should enable governed self-service, not analytics chaos.
