Dbt Transformation Patterns

dbt Transformation Patterns

Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.

Use this skill when

• Building data transformation pipelines with dbt
• Organizing models into staging, intermediate, and marts layers
• Implementing data quality tests and documentation
• Creating incremental models for large datasets
• Setting up dbt project structure and conventions

Do not use this skill when

• The project is not using dbt or a warehouse-backed workflow
• You only need ad-hoc SQL queries
• There is no access to source data or schemas

Instructions

• Define model layers, naming, and ownership.
• Implement tests, documentation, and freshness checks.
• Choose materializations and incremental strategies.
• Optimize runs with selectors and CI workflows.
• If detailed patterns are required, open resources/implementation-playbook.md.

Resources

• resources/implementation-playbook.md for detailed dbt patterns and examples.

When to Use

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.