
This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
| Publishes | Twice monthly | Episodes | 516 | Founded | 10 years ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | TechnologyEducation | |||

Summary
In this episode Yetunde Dada discusses Otto, Astronomer’s AI agent for Airflow, and the broader challenge of making agentic tooling actually useful for data engineers. She explored why generic coding assistants often fall short in data workf... more
Summary
In this episode Ragnor Comerford talks about OmniGraph, a lakehouse-native graph storage layer designed around the needs of agentic systems. He explores how graphs are primarily a semantic model for representing the world, rather than just a... more
Summary
In this episode Prukalpa Sankar, co-founder of Atlan, talks about what it takes to build a “context flywheel” for AI agents in data-intensive organizations. She explained why model intelligence alone isn’t enough to make AI useful in product... more
Summary
In this episode Jevin Maltais talks about the practical realities of building reliable, product-focused streaming systems with Kafka. Jevin shares lessons from roles at Zapier, Humi, and Clio, where real-time synchronization, customer data u... more
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No one absolutely no one goes in depth of anything in this podcast, everyone only come and talk about their tools.
Always worth listening to understand what problems people are dealing with and considering how I can apply these lessons to my data engineering.
I really enjoy this podcast and learn a lot from it. I wonder why none of data tools in Azure is never mentioned.
Thanks
When you are looking for more knowledge and clarity in the world of data engineering/management, then you have come to the right place.
Tobias does a great job covering the future of data engineering - practical tips, the future of the industry with the founders of new tools, and no-nonsense advice on how to build data pipelines, viz, and process that will scale.
Key themes from listener reviews, highlighting what works and what could be improved about the show.
How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.
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Apple Podcasts | #214 |
Recent interactions between the hosts and their guests.
Listeners, social reach, demographics and more for this podcast.
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A technically oriented program that centers on data engineering tooling, architectures, and best practices. Episodes frequently explore topics like data pipelines, streaming, governance, metadata, and AI-infused data platforms, with guests ranging from startup founders to platform leaders and researchers. The show tends to favor deep-dive conversations about real-world systems, scale, and the trade-offs of different data architectures, often highlighting practical patterns, tooling comparisons, and governance considerations. Noteworthy traits include a strong focus on cutting-edge approaches (e.g., lakehouse, agent-based workflows, reproducible science) and a clear emphasis on actionable insights for practitioners responsible for building r... more
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These podcasts share a similar audience with Data Engineering Podcast:
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4. Software Engineering Daily
5. Software Engineering Radio - the podcast for professional software developers
Data Engineering Podcast launched 10 years ago and published 516 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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Recent guests on Data Engineering Podcast include:
1. Ragnor Comerford
2. Prakulpa Sankar
3. Jevin Maltais
4. Shravan Gunda
5. Weimo Liu
6. Robert Nishihara
7. Himant Goyal
8. Rowan Cockett
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