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.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.