Dbt Transformation Patterns

A solid collection of dbt patterns that actually follows modern analytics engineering practices. Sets up proper medallion architecture with staging, intermediate, and marts layers, plus realistic examples of incremental models, source freshness checks, and relationship tests. The naming conventions and folder structure match what you'd see in production teams. Covers the tricky parts like handling schema changes in incremental models and generating surrogate keys. If you're moving beyond basic dbt tutorials and need patterns that scale beyond toy datasets, this gives you the scaffolding to build maintainable data pipelines.

skills.sh installs: 11.3K
GitHub stars: 42.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add wshobson/agents --skill dbt-transformation-patterns --agent claude-code

Installs into .claude/skills of the current project.

Files

dbt Transformation Patterns

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

When to Use This Skill

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

Core Concepts

1. Model Layers (Medallion Architecture)

sources/          Raw data definitions
    ↓
staging/          1:1 with source, light cleaning
    ↓
intermediate/     Business logic, joins, aggregations
    ↓
marts/            Final analytics tables