10 Data Engineering Podcasts You Should Follow in 2026
The world of data engineering moves fast. One week, everyone is talking about Spark. The next week, it is all about Iceberg, DuckDB, or AI-powered pipelines. If you are not constantly learning, you are falling behind.
But who has time to read blogs and documentation all day? That is where podcasts come in. They let you learn from industry leaders while commuting, exercising, or doing chores.
Here are the 10 data engineering podcasts you should have in your rotation in 2026—curated for practical insights, career growth, and staying ahead of the curve.
1. The Data Engineering Show
Hosts: Benjamin Wagner, Eldad Farkash, Boaz Farkash
Frequency: Weekly
This podcast is a must-listen for data engineering and BI practitioners who want to go beyond theory. Hosts sit down with the biggest influencers in tech to discuss practical, day-to-day data challenges and solutions in a casual and fun setting.
Why it stands out: The show covers the intersection of AI and data engineering with episodes like "AI for Data and Data for AI: The Dual Frontier of Modern Data Engineering"—which explores why you need to master both sides to stay relevant in 2026. Recent guests include engineers from Canva, Airbnb, and Cloudflare, offering real-world insights on scaling ML for millions of users and building distributed systems across 300 global locations.
Best for: Engineers who want to understand how AI is reshaping data engineering roles and what tools are defining the next-gen data stack.
2. Data Engineering Podcast
Host: Tobias Macey
Frequency: Weekly
Rating: 4.6 Apple, 4.7 Spotify (511+ reviews)
This show goes behind the scenes for the tools, techniques, and difficulties associated with data engineering. With over 500 episodes, Tobias Macey covers everything from databases and workflows to automation and data manipulation.
Why it stands out: It is one of the longest-running and most respected shows in the space. Recent episodes feature deep dives into practical topics like zero-copy ETL with PuppyGraph, the AI-first data engineer (promising 10-50x productivity improvements), and optimizing GPU utilization with Ray and Kubernetes. The show also provides a free data engineering interview prep platform for listeners.
Best for: Practitioners who want deep technical conversations on real-world platform decisions, tradeoffs, and tooling.
3. Data Engineering Central Podcast
Hosts: Daniel Beecher, Daniel Beach
Frequency: Weekly (30 episodes published)
This podcast takes a pragmatic, no-holds-barred approach to data engineering news, topics, and general mayhem. It focuses heavily on lakehouse architectures, open-source projects, SQL and Python ecosystems, and practical career guidance.
Why it stands out: The show is deeply practical. Recent episodes explore DuckDB, the real story behind data engineering careers in Big Tech, and what actually matters in data (hosts have featured Matthew Housley, co-author of Fundamentals of Data Engineering). The host-guest dynamics are candid, and the show consistently emphasizes fundamentals and open-source contributions.
Best for: Hands-on data engineers evaluating next-generation stacks and seeking pragmatic career advice.
4. Data Brew by Databricks
Host: Databricks Team
Frequency: Regular
This podcast comes directly from Databricks, one of the biggest players in the data space. It covers everything from Apache Spark and Delta Lake to the latest in lakehouse architecture and AI.
Why it stands out: You get insights straight from the source. Whether it is new features in the Databricks platform or broader trends in data engineering, this show keeps you informed about what is happening at the bleeding edge.
Best for: Anyone working with the Databricks ecosystem or interested in lakehouse technologies.
5. The Data Cloud Podcast by Snowflake
Host: Snowflake Team
Frequency: Regular
Snowflake's official podcast covers the data cloud ecosystem, including data engineering, analytics, and AI. It features conversations with customers, partners, and internal experts.
Why it stands out: Like Data Brew, this podcast gives you an inside look at one of the most influential platforms in the industry. You will hear about real-world use cases, best practices, and where the platform is heading.
Best for: Snowflake users and anyone interested in cloud data platforms.
6. Streaming Audio by Confluent
Host: Confluent Team
Frequency: Regular
This podcast focuses on the world of real-time data streaming with Apache Kafka and the Confluent ecosystem.
Why it stands out: Streaming is becoming table stakes for modern data engineering. This show helps you understand how to build, scale, and troubleshoot streaming architectures from the company behind Kafka.
Best for: Data engineers building real-time pipelines.
7. The Data Stack Show
Hosts: Kostas Pardalis, Eric Dodd
Frequency: Regular
This show interviews an impressive number of CEOs and founders in the data industry. While databases are not the main thrust, the hosts carve out significant air time on storage engines, analytics, and industry trends.
Why it stands out: It gives you a high-level strategic perspective on where the data industry is heading. Recent episodes cover Materialize and timely dataflow. It is great for understanding the business and product side of data technology.
Best for: Engineers who want to understand the broader ecosystem and where the industry is going.
8. Data talks club
Host: DataTalks Team
Frequency: Regular
This podcast comes from the popular community. It features conversations with data professionals about their careers, projects, and lessons learned.
Why it stands out: It is community-driven and highly accessible. Episodes cover a wide range of topics from entry-level advice to advanced technical discussions.
Best for: Learning from a diverse range of voices in the data community.
9. Drill to Detail with Mark Rittman
Host: Mark Rittman
Frequency: Regular
This podcast focuses heavily on database analytics and reporting. Episodes cover real-time stream processing, data quality, metadata, and more.
Why it stands out: It is a favorite among analysts and BI professionals who want to glean deeper insights from data. It is for the strategist who sees patterns others miss.
Best for: Data analysts and analytics engineers focused on reporting and business intelligence.
10. TechJobber Podcast
Host: Chris Schwenk
Frequency: Weekly
This podcast helps students and professionals build successful careers in technology through career roadmaps and interviews with industry leaders, including a recent episode on how to become a data engineer in 2026.
Why it stands out: It offers insider hiring strategies from someone who has actually placed people in data roles. Episodes cover Snowflake vs. Databricks, certifications, whether AI will replace data engineers, and business skills every data engineer needs.
Best for: Aspiring data engineers, career switchers, and anyone navigating the job market.
Quick Reference Table
| Podcast | Best For | Key Focus |
|---|---|---|
| The Data Engineering Show | AI + Data intersection | AI for data, real-world scaling, industry leaders |
| Data Engineering Podcast | Deep technical dives | Tools, techniques, 500+ episodes |
| Data Engineering Central | Pragmatic career + tooling | Lakehouse, open-source, career growth |
| Data Brew by Databricks | Databricks ecosystem | Spark, Delta Lake, AI |
| The Data Cloud Podcast | Snowflake ecosystem | Data cloud, analytics, AI |
| Streaming Audio | Real-time streaming | Kafka, streaming architectures |
| The Data Stack Show | Industry strategy | Data industry trends, founders, CEOs |
| DataTalks.Club | Community + diverse voices | Career lessons, broad topics |
| Drill to Detail | Analytics + BI | Reporting, data quality, analytics |
| TechJobber Podcast | Career growth | Job market, skills, hiring strategies |
How to Choose Where to Start
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If you have limited time: Pick The Data Engineering Show or Data Engineering Central—they are highly practical and cover current trends.
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If you are job hunting: Listen to TechJobber Podcast for hiring insights and Data Engineering Podcast for its free interview prep platform.
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If you want strategy: Try The Data Stack Show for high-level industry perspectives.
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If you work with specific platforms: Follow Data Brew (Databricks) or The Data Cloud Podcast (Snowflake) for platform-specific insights.
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If you love open-source: Data Engineering Central frequently covers open-source projects like DuckDB, Delta Lake, and Iceberg.
The Bottom Line
There is no single "best" podcast—the best one is the one that fits your learning style and career goals. The key is to start somewhere. Pick two shows from this list that resonate with you, subscribe, and commit to listening to one episode per week.
The data engineering landscape is shifting fast. In 2026, AI is not just a buzzword—it is fundamentally reshaping roles, automating entry-level tasks, and raising the bar for what it means to be a data engineer. Podcasts are your shortcut to staying informed without spending hours reading documentation.
Make learning a habit. Your career will thank you.
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