andre-salvati/databricks-template

databricks-template — agentic development for Databricks + production-ready ETL

🚀 Overview

Stop spending weeks on boilerplate. This PySpark project template for Databricks gives you medallion architecture, Python packaging, unit + integration + load tests, CI/CD via Declarative Automation Bundles, DQX data quality, and service-principal-based production deploys — all wired together and ready to ship. Whether you're starting a new Databricks ETL project or looking for a reference implementation of production-ready PySpark pipelines, fork this and go.

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🧪 Technologies

• Databricks Free Edition (Serverless)
• Databricks Runtime 18.0 LTS
• Databricks Unity Catalog
• Databricks Declarative Automation Bundles (former Asset Bundles)
• Databricks CLI
• Databricks Python SDK
• Databricks DQX
• Databricks AI Dev Kit
• Databricks Dashboards
• Claude Code
• PySpark 4.1
• Spark Declarative Pipelines (SDP)
• Python 3.12+
• GitHub Actions
• Pytest

📦 Features

This project template demonstrates how to:

• use agentic development (with Databricks AI Dev Kit and Claude Code) in data projects. The template ships with a CLAUDE.md that documents the project's conventions.
• structure PySpark code inside classes/packages, deploy it as a Python wheel (instead of notebooks), and manage the project with uv.
• package and deploy code with [Declarat