Can this skill help with data quality and testing?

Yes, it provides automated patterns for unique, not_null, and relationship tests, as well as custom logic for business rule validation.

What is the recommended project structure for dbt?

The skill enforces a best-practice directory structure including staging (raw source wrappers), intermediate (reusable logic), and marts (consumption-ready entities).

Does this skill handle data ingestion (ELT)?

No, this skill focuses specifically on the transformation layer. It assumes data has already been loaded into the warehouse via tools like Fivetran or Airbyte.

Which data warehouses are supported by this skill?

The skill follows standard dbt and SQL patterns compatible with major warehouses including Snowflake, BigQuery, Redshift, and Databricks.

How does it handle large datasets?

It implements incremental materialization patterns and partitioning strategies to ensure efficient processing of tables with millions of rows.

Analytics Engineer

Name: Analytics Engineer
Author: borghei

byborghei

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分析と監視

Builds scalable dbt transformation layers and dimensional models to transform raw warehouse data into actionable business insights.

This skill empowers Claude to act as a senior analytics engineer, specializing in the modern data stack. It provides specialized workflows for designing Kimball-style dimensional models, writing modular SQL within dbt (Data Build Tool), and implementing rigorous data testing frameworks. Whether you are building a new data mart from scratch, optimizing warehouse query performance, or defining standardized business metrics in a semantic layer, this skill ensures your data pipeline follows industry best practices for maintainability and accuracy.

主な機能

01Dimensional data modeling using star and snowflake schema patterns

02Semantic layer configuration for standardized metric definitions

03SQL performance optimization and incremental materialization strategies

04Automated dbt model generation for staging, intermediate, and mart layers

0550 GitHub stars

06Robust data testing and YAML-based documentation automation

ユースケース

01Implementing Slim CI workflows to reduce warehouse costs during development

02Refactoring monolithic SQL scripts into modular, tested dbt projects

03Defining a 'Single Source of Truth' for business metrics using the dbt Semantic Layer

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add borghei/claude-skills analytics-engineer

For use in Claude.ai and ChatGPT

Download Skill