SQL Is Still Your Superpower: Building Production Ready Data Pipelines Using Only SQL

SQL didn’t get weaker, data platforms got better.

In this session, we demonstrate how modern data engineering on Databricks can be delivered end-to-end using SQL alone on the Lakehouse, without dependency on Python or external frameworks, including SQL AI functions and Geospatial Functions. Designed for organisations with strong BI/SQL foundations, this session shows how to transition to production-grade data engineering with minimal upskilling.

We showcase how pipelines are built using Lakeflow Spark Declarative Pipelines via the Pipeline Editor, with ingestion, transformation, and data quality rules all defined declaratively in SQL. This demonstrates how SQL moves beyond querying into full pipeline engineering.

Governance is implemented by design using Unity Catalog, providing fine-grained permissions, lineage, and auditability across the entire pipeline. We also showcase AI/BI Genie, configured using SQL-only approaches (metrics, dimensions, instructions, and evaluation queries), enabling natural language access to trusted data.

This session reframes SQL as a first-class engineering language on the Lakehouse, capable of handling streaming, transformation, data quality, governance, and AI consumption, while unlocking existing talent and accelerating adoption without increasing complexity.