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Advanced Claude Code Workflows for dbt

A reading path through Claude Code configuration, testing, documentation, and debugging workflows for analytics engineers working with dbt on BigQuery

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claude codedbtbigquerydata engineeringaiautomation

This hub covers how to configure Claude Code for dbt projects and use it for testing, documentation, and debugging — six notes covering systematic, repeatable workflows. Assumes familiarity with Claude Code basics and dbt on BigQuery.

Prerequisites

  • Claude Code installed and functional
  • A dbt project targeting BigQuery
  • Familiarity with basic Claude Code usage (prompting, file editing, command execution)

Reading Order

Foundation

  1. CLAUDE.md as Project Memory — How to give Claude persistent project context. Covers the reactive approach to building CLAUDE.md that converges on instructions that actually matter.

  2. Claude Code Hooks — Deterministic guardrails that enforce rules regardless of prompting: auto-format SQL, block edits to production files, trigger compilation after changes.

  3. Claude Code Slash Commands for dbt — Reusable, team-shareable commands for common workflows; turns multi-step prompts into single invocations.

Workflows

  1. TDD with Claude Code for dbt — Five-step test-driven development pattern: write tests first, let the agent iterate to green, refactor.

  2. dbt Documentation with Claude Code — The codegen-plus-AI pattern for model documentation, docs blocks for cross-model consistency, and Mermaid lineage diagrams.

  3. Debugging dbt with Claude Code — Letting Claude face errors directly rather than pre-gathering evidence; subagents for complex investigations that need fresh context.