In this episode of the Data Engineering Central Podcast, I sit down with David Jaitillake to explore the future of data engineering, analytics, and AI. David has spent nearly two decades working across data teams, from analyst roles in the early SQL Server days to leading teams, founding startups, serving as VP of AI at Cube, and now co-founding Quarry.
We discuss why semantic layers have suddenly become one of the most important concepts in modern data platforms, how tools like Claude Code are transforming engineering workflows, and why the core problems in data haven’t really changed despite massive advances in technology.
David shares his perspective on where agentic workflows are headed, what AI means for junior engineers entering the field, and why experienced practitioners may be more valuable than ever before. We also dive into the evolution of data platforms, lessons learned from startups, the promise of tools like DuckDB and MotherDuck, and how organizations should think about adopting AI responsibly.
Whether you’re a data engineer, analytics engineer, engineering leader, or someone trying to understand where the industry is headed, this conversation offers a practical and honest look at what’s coming next.
What We Cover
David’s journey from analyst to startup founder
The rise of semantic layers and why they matter
Why data modeling is still critical in the AI era
How AI coding agents are changing engineering work
What Claude Code is enabling today
The future of agentic data pipelines
Why DuckDB and MotherDuck are gaining traction
The challenges facing junior engineers
Career advice for data professionals at every stage
Whether David is optimistic about the future of AI and data
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