Does this skill help with Unity Catalog setup?

Yes, it provides SQL and configuration templates to define catalogs, schemas, and granular permissions for data governance.

Can I use this for existing projects?

Absolutely. Use it to review your current architecture against best practices or to establish new standards for existing workspaces.

What is the Medallion Architecture supported by this skill?

It implements a three-layer data design: Bronze (raw ingestion), Silver (cleaned/filtered data), and Gold (business-ready aggregated data).

How does it handle Databricks deployments?

It uses Databricks Asset Bundles (DABs) to define infrastructure as code, including jobs, clusters, and pipeline configurations.

Databricks Reference Architecture

Name: Databricks Reference Architecture
Author: micsapp

bymicsapp

0•

Data Science & ML

Implements production-ready Databricks Lakehouse architectures using the medallion pattern, Unity Catalog, and Delta Lake.

This skill enables developers to rapidly scaffold and audit Databricks projects following industry-standard reference architectures. It automates the setup of Unity Catalog hierarchies, configures medallion pattern (bronze/silver/gold) structures, and provides standardized Databricks Asset Bundle (DAB) configurations for reliable CI/CD. Whether you are starting a new data engineering project or reviewing an existing one, this skill ensures best practices for data governance, storage, and compute are consistently applied across your enterprise data platform.

Key Features

01Production-ready infrastructure templates for jobs and clusters

02Unity Catalog hierarchy and permission management configuration

03Delta Lake ingestion and transformation implementation patterns

040 GitHub stars

05Standardized medallion architecture (bronze/silver/gold) project layouts

06Databricks Asset Bundle (DAB) setup for automated deployments

Use Cases

01Implementing automated CI/CD pipelines for Spark-based ETL jobs

02Scaffolding a new enterprise-grade Databricks data platform

03Standardizing data governance and access control via Unity Catalog

Key Features

01Production-ready infrastructure templates for jobs and clusters

02Unity Catalog hierarchy and permission management configuration

03Delta Lake ingestion and transformation implementation patterns

040 GitHub stars

05Standardized medallion architecture (bronze/silver/gold) project layouts

06Databricks Asset Bundle (DAB) setup for automated deployments

Use Cases

01Implementing automated CI/CD pipelines for Spark-based ETL jobs

02Scaffolding a new enterprise-grade Databricks data platform

03Standardizing data governance and access control via Unity Catalog