What is the medallion architecture used in this skill?

It is a data design pattern that organizes data into three layers: Staging (raw cleaning), Intermediate (business logic joins), and Marts (final analytics-ready tables like facts and dimensions).

How does it handle data quality?

It provides standardized patterns for schema tests, relationship testing, and dbt_utils expressions to ensure data integrity and observability.

Does this skill help with processing large datasets?

Yes, it includes detailed patterns for incremental models, partitioning strategies, and merge/overwrite logic to optimize performance on high-volume data.

Can I use this for complex SQL macros?

Absolutely. It includes patterns for creating custom Jinja macros to handle repetitive logic, such as currency conversion or environment-based data limiting.

DBT Transformation Patterns

Name: DBT Transformation Patterns
Author: as4584

byas4584

0•

Database Management

Implements production-ready dbt patterns for scalable data transformation, model organization, and analytics engineering best practices.

This skill equips Claude with standardized patterns for the data build tool (dbt), enabling the creation of robust analytics pipelines using the medallion architecture. It provides expert guidance on organizing models into staging, intermediate, and marts layers, implementing complex incremental strategies, and maintaining high data quality through automated testing and documentation. Whether you are bootstrapping a new dbt project or refactoring existing transformations, this skill ensures best practices for performance, maintainability, and data lineage are followed across your entire data warehouse.

Key Features

01Medallion architecture implementation (Staging, Intermediate, Marts)

02Advanced incremental processing strategies including Merge and Insert Overwrite

03Comprehensive data testing and source freshness configurations

040 GitHub stars

05Standardized naming conventions and project directory structures

06Reusable Jinja macros for DRY (Don't Repeat Yourself) SQL code

Use Cases

01Building a scalable and documented data warehouse from scratch using dbt

02Implementing data quality frameworks and automated testing in analytics pipelines

03Optimizing long-running SQL transformations with incremental materialization

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add as4584/antigravity-skills dbt-transformation-patterns

For use in Claude.ai and ChatGPT

Download Skill