The Evolution of Data Engineering in the AI Era
About this session
**The Evolution of Data Engineering in the AI Era**
Artificial intelligence is fundamentally reshaping the role of data engineering. Traditional data platforms were designed to support reporting, business intelligence, and historical analytics. Today's AI-native organizations require something entirely different: real-time data pipelines, scalable infrastructure, high-quality feature stores, observability, governance, and data products that power intelligent applications.
This session explores how the discipline of data engineering has evolved to meet the demands of modern AI companies. Drawing from real-world experiences building data platforms at high-growth AI organizations, we'll examine how data engineers are moving beyond ETL development to become architects of the infrastructure that enables machine learning, generative AI, and autonomous agents.
Speaker
Key takeaways
- Understand how AI is transforming the role of data engineering from traditional analytics support to powering intelligent, real-time AI applications.
- Learn practical strategies for building scalable, reliable data platforms that enable AI products, machine learning, and autonomous agents.
- Discover the emerging skills, architectures, and best practices that will define the next generation of data engineering in AI-first organizations.