Spark, Lakehouse & AI: A Deep Conversation with Bart Konieczny
From Data Engineering Central Podcast by Data Engineering in Real Life
February 25, 2026 · 45 min
About this episode
A deep technical conversation with Bart Konieczny about modern data engineering, covering topics like Spark internals, lakehouse architecture, and AI's impact on the field.
In this episode of Data Engineering Central, I sit down with Bart Konieczny — data engineer, distributed systems expert, and well-known author in the Data and Spark ecosystem — for a deep technical conversation about modern data engineering. We cover: * How Bart got into tech and distributed systems * His journey through different engineering roles * Spark internals and why they still matter * The realities of lakehouse architecture * Streaming vs batch systems * AI’s impact on data engineering * What engineers should focus on in 2026 In a world obsessed with abstractions and AI tooling, we explore whether understanding the internals is still worth it — or if the game has fundamentally changed. If you’re a data engineer, architect, or platform leader trying to navigate the next phase of the lakehouse era, this one’s for you. Thanks for reading Data Engineering Central! This post is public so feel free to share it. — 🎙️ Data Engineering Central PodcastHosted by Daniel Beach If you’re a CTO or data leader looking for help building or optimizing your data platform, reach out — consulting inquiries welcome. Data Engineering Central is a reader-supported publication. To receive new…
People in this episode
Host: Daniel Beach
Guest: Bart Konieczny
Topics covered
- data engineering
- lakehouse architecture
- AI impact
- Spark internals
- streaming vs batch systems
- engineering roles
Keywords
- data engineering
- lakehouse
- AI
- Spark
- streaming
- batch systems
- distributed systems
Mentioned in this episode
Organizations: Data Engineering Central, Spark
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