talk-data.com talk-data.com

Michael Armbrust

Speaker

Michael Armbrust

5

talks

Distinguished Engineer Databricks

Michael Armbrust is a committer and PMC member of Apache Spark and the original creator of Spark SQL, Structured Streaming, and Delta Lake. He currently tech-leads the Lakeflow organization at Databricks, with research interests in distributed systems, large-scale structured storage, and query optimization.

Bio from: Data + AI Summit 2025

Frequent Collaborators

Filtering by: Data + AI Summit 2025 ×

Filter by Event / Source

Talks & appearances

Showing 5 of 12 activities

Search activities →
Getting the Most Out of Lakeflow Declarative Pipelines: A Deep Dive on What’s New and Best Practices

This deep dive covers advanced usage patterns, tips and best practices for maximizing the potential of Lakeflow Declarative Pipelines. Attendees will explore new features, enhanced workflows and cost-optimization strategies through a demo-heavy presentation. The session will also address complex use cases, showcasing how Lakeflow Declarative Pipelines simplifies the management of robust data pipelines while maintaining scalability and efficiency across diverse data engineering challenges.

keynote
with Bilal Aslam (Databricks) , Michael Armbrust (Databricks) , Arsalan Tavakoli-Shiraji (Databricks) , Miranda Luna (Databricks) , Michael Flynn (Rivian) , Ken Wong (Databricks) , Ali Ghodsi (Databricks) , Keegan Dubbs (Databricks) , Matei Zaharia (Databricks) , Michelle Leon (Databricks) , Michael Piatek (Databricks)

Discover the latest advances on the Data Intelligence Platform and hear from the companies who are already enjoying success.

Declarative Pipelines: What’s Next for the Apache Spark Ecosystem

Lakeflow Declarative Pipelines has made it dramatically easier to build production-grade Spark pipelines, using a framework that abstracts away orchestration and complexity. It’s become a go-to solution for teams who want reliable, maintainable pipelines without reinventing the wheel.But we’re just getting started. In this session, we’ll take a step back and share a broader vision for the future of Spark Declarative Pipelines — one that opens the door to a new level of openness, standardization and community momentum.We’ll cover the core concepts behind Declarative Pipelines, where the architecture is headed, and what this shift means for both existing Lakeflow users and Spark engineers building procedural code. Don’t miss this session — we’ll be sharing something new that sets the direction for what comes next.

Introducing Lakeflow: The Future of Data Engineering on Databricks

Join us to explore Lakeflow, Databricks' end-to-end solution for simplifying and unifying the most complex data engineering workflows. This session builds on keynote announcements, offering an accessible introduction for newcomers while emphasizing the transformative value Lakeflow delivers.We’ll cover: What is Lakeflow? – A cohesive overview of its components: Lakeflow Connect, Lakeflow Declarative Pipelines, and Lakeflow Jobs. Core Capabilities in Action – Live demos showcasing no-code data ingestion, code-optional declarative pipelines, and unified, end-to-end orchestration. Vision for the Future – Unveil the roadmap, introducing no-code and open-source initiatives. Discover how Lakeflow equips data teams with a seamless experience for ingestion, transformation, and orchestration, reducing complexity and driving productivity. By unifying these capabilities, Lakeflow lays the groundwork for scalable, reliable, efficient data pipelines in a governed and high-performing environment.