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R

Speaker

Ritwik Yadav

1

talks

Software Engineer Databricks

Ritwik is passionate about solving efficiency problems in large-scale database systems. He currently leads the team at Databricks that built the incremental view maintenance engine, enabling low-latency, cost-efficient materialized views over massive data. Before Databricks, Ritwik led the Self-Managing Databases group at Facebook, where he tackled critical efficiency challenges in the world’s largest MySQL deployment.

Bio from: Data + AI Summit 2025

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SQL-First ETL: Building Easy, Efficient Data Pipelines With Lakeflow Declarative Pipelines

This session explores how SQL-based ETL can accelerate development, simplify maintenance and make data transformation more accessible to both engineers and analysts. We'll walk through how Databricks Lakeflow Declarative Pipelines and Databricks SQL warehouse support building production-grade pipelines using familiar SQL constructs.Topics include: Using streaming tables for real-time ingestion and processing Leveraging materialized views to deliver fast, pre-computed datasets Integrating with tools like dbt to manage batch and streaming workflows at scale By the end of the session, you’ll understand how SQL-first approaches can streamline ETL development and support both operational and analytical use cases.