Session
Building Production-Grade SQL ETL on the Lakehouse
Overview
| Experience | In Person, Virtual |
|---|---|
| Track | Data Warehousing |
| Industry | Enterprise Technology |
| Technologies | Databricks SQL |
| Skill Level | Beginner |
ETL pipelines are often the most brittle part of the analytics stack — spread across tools, written in multiple languages, and hard to operate at scale. This session shows how teams build production-grade SQL ETL on Databricks Lakehouse using a unified, SQL-first approach. We’ll cover how to ingest, transform, and manage data using declarative pipelines, apply governance and quality controls consistently, author and optimize with AI, and deliver reliable datasets directly to analytics and downstream workloads. The focus is on simplifying architecture, reducing operational overhead, and enabling faster iteration without sacrificing correctness or scale.
Session Speakers
Mengfei Ren
/Engineering Manager
Databricks
Shanelle Roman
/Senior Product Manager
Databricks