Data Data Lakehouse

Purpose

Design lakehouse architectures that merge data lake flexibility with warehouse reliability. Implement medallion architecture for data quality progression, Unity Catalog for governance, Delta Sharing for data collaboration, and multi-cloud deployment patterns.

Agent Protocol

Trigger

Exact user phrases: "lakehouse", "medallion architecture", "bronze", "silver", "gold", "Databricks", "Unity Catalog", "Delta Sharing", "Apache Paimon", "multi-cloud lakehouse", "open formats", "lakehouse governance", "data mesh lakehouse".

Input Context

Before activating, verify:

• Cloud provider (AWS, Azure, GCP, multi-cloud)
• Lakehouse platform (Databricks, AWS EMR, Azure Synapse, GCP Dataproc)
• Table format (Delta, Iceberg, Paimon)
• Data sources volume and types
• Number of data producers and consumers
• Security requirements (RBAC, column mask, row filter)
• Data sharing requirements (internal teams, external partners)