The Data Engineering Show - Podcast
A technical podcast where a Firebolt engineer interviews practitioners from top tech companies about their data and AI infrastructure.
This is a show for practicing engineers, by a practicing engineer. It bypasses high-level theory to get into the weeds of tech stacks, architectural decisions, and the real-world problems of scaling data and AI systems at companies like Airbnb, Canva, and Cloudflare.
“Unlike broader tech podcasts, it maintains a laser focus on the data and ML infrastructure layer. The host's own deep expertise as a query engine lead allows for highly specific, technical questioning that goes beyond surface-level discussions.”
Who hosts this show
The Data Engineering Show features deep-dive interviews with data and ML engineers from leading tech companies. Season 2 is hosted by Benjamin Wagner, who leads query processing at Firebolt and holds an MS in Computer Science. He took over from Season 1 hosts Eldad and Boaz Farkash, the founders of Sisense and Firebolt. The show explores the practical challenges and solutions in data engineering, ML, and AI infrastructure.
Credentials & credits
- CEO at Firebolt
- VP of Engineering at Firebolt
- Leads query processing team at Firebolt
- MS, Computer Science
- Studied at TU Munich
Other ventures
- Firebolt
What kind of podcast
- Country
- United States
- Region
- usa
When new episodes drop
- 01
- 02
- 03
- 04
- 05The Framework Canva Uses for 200M+ Designers with Paul TuneApr 28, 2026 · 27 min
- 06Llama 2 & 3 Safety: Soumya Batra on Agentic AI TrainingApr 8, 2026 · 25 min
- 07The Data Fusion Secret & Why Custom Query Engines Fail with Nikita LapkovMar 24, 2026 · 23 min
- 08
Notable episodes
- 01AI Won't Replace Engineers, But This Framework Will Change How They Build with Rohit Girme
A deep dive into how Airbnb built a dedicated platform to evaluate generative AI models, illustrating the real-world challenges of moving from AI theory to production.
- 02The Framework Canva Uses for 200M+ Designers with Paul Tune
Explores the data and ML infrastructure at Canva, detailing their full tech stack and how they serve a massive, diverse user base from novices to experts.
- 03AI for Data and Data for AI: The Dual Frontier of Modern Data Engineering ft. Pranav Motarwar
Clearly articulates the emerging split in data engineering into two domains: using AI to improve data processes and building data systems to serve AI applications.
What you'll be asked on this show
Wagner typically opens by asking guests for a brief self-introduction before diving into their current work and top-of-mind challenges. He uses detailed, multi-part questions to probe the specifics of a guest's tech stack, architecture, and team structure. He frequently synthesizes a guest's answer to formulate a more precise follow-up, often grounding abstract concepts in concrete examples. Towards the end of the conversation, he transitions from granular technical details to broader, forward-looking questions about the industry and the craft of engineering.
A one-on-one interview show hosted by Benjamin Wagner. Episodes begin with a detailed introduction of the guest and topic, followed by a deep dive into technical architecture. The show also releases short highlight clips from the longer interviews. The podcast is produced by Firebolt, the host's employer, which is the sole sponsor.
Questions the host keeps coming back to
12 cataloguedIf you're going on this show as a guest, expect some version of each of these. Each note explains when the host reaches for it.
origin
1- Q.01
“Can you introduce yourself and tell listeners what you're working on?”
This is his standard opening to establish the guest's credentials and current focus.
process
5- Q.01
“What projects are you working on at the moment? What's top of mind?”
A follow-up to the intro that hones in on the guest's immediate technical challenges.
- Q.02
“How does serving different audiences affect your ML models and training?”
Connects the user base or business problem directly to technical implementation strategy.
- Q.03
“What's a concrete example of that feature and how does it connect to your platform?”
A frequent move to ground abstract architectural concepts in a real-world application.
- Q.04
“How do you structure your ML teams to handle prototyping versus production?”
Explores the organizational and workflow aspects of building and maintaining ML systems.
- Q.05
“How does organizational learning work for your team in this new world of AI tools?”
Asks about the process of sharing knowledge and best practices within the guest's team.
craft
2- Q.01
“Can you walk us through the tech stack for your project?”
Used to get a detailed breakdown of the specific technologies and architecture in use.
- Q.02
“Where are the biggest performance bottlenecks in your ML pipelines?”
This question targets the critical pain points and performance challenges in a guest's system.
future
3- Q.01
“How is recent ML and AI changing design and engineering at your company?”
A forward-looking question to explore the impact of new technology on the guest's domain.
- Q.02
“What's on your roadmap for the next few months that you're excited about?”
Probes for the guest's future direction and technical priorities.
- Q.03
“What are you excited about for the future of engineering workflows as AI tools improve?”
A common closing question to elicit a broader, forward-looking perspective on the industry.
advice
1- Q.01
“How do you personally keep up with the rapid changes in ML and AI technology?”
Asked near the end of the interview to get personal advice and habits from the expert guest.
Topics covered repeatedly
Who gets booked here
Staff-level or higher engineers, researchers, and technical founders from major tech companies (e.g., Airbnb, Canva, Meta) and high-growth startups who are actively building and scaling data and AI systems.
- Pranav Nitin Motarwaron AI for Data and Data for AI: The Dual Frontier of Modern Data Engineering ft. Pranav Motarwar
- Rohit Girmeon AI Won't Replace Engineers, But This Framework Will Change How They Build with Rohit Girme
- Paul Tuneon The Framework Canva Uses for 200M+ Designers with Paul Tune
- Soumya Batraon Llama 2 & 3 Safety: Soumya Batra on Agentic AI Training
- Nikita Lapkovon The Data Fusion Secret & Why Custom Query Engines Fail with Nikita Lapkov
- Nikhil Simhaon How Zipline AI Turns Weeks of Engineering Into Minutes of SQL Queries ft. Nikhil Simha
Where to find this show
Audience & reach
The show is sponsored and produced by Firebolt, a cloud data warehouse company. The current host, Benjamin Wagner, is the CEO of Firebolt, and the previous hosts were the company's founders. The content is highly relevant to Firebolt's target audience of data engineers.
Subscriber and view counts are pulled live from YouTube and re-verified on a 30-day cycle. Listener estimates for the RSS feed aren't published here unless they're host-verified.
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People also ask
- Who is the host of The Data Engineering Show?
- The current host (Season 2) is Benjamin Wagner, the CEO of Firebolt. The first season was hosted by Firebolt founders Eldad and Boaz Farkash.
- Is the podcast still running?
- Yes, the podcast releases new episodes, typically on a weekly or bi-weekly basis.
- What is the format of the show?
- It is a one-on-one interview show featuring conversations with senior engineers and researchers from other tech companies about their data and AI infrastructure.
- Who is this podcast for?
- The show is aimed at practicing data engineers, ML engineers, and technical leaders interested in the low-level details of modern data and AI stacks.
- What is the podcast's connection to Firebolt?
- The podcast is produced by Firebolt. The current host, Benjamin Wagner, is Firebolt's CEO, and the original hosts were the company's founders.
- Where can I listen to the podcast?
- The Data Engineering Show is available on YouTube, Apple Podcasts, and Spotify.
Built from the show's public RSS feed, YouTube, the host's own websites, and the cited sources below. Computed and AI-extracted fields are labelled. Facts only — no private info, no fabrication, no transcripts republished.
Sources & how this page was built
This page is AI-assisted, grounded in the public sources cited below, and host-verifiable. We publish facts only; we do not republish transcripts. If anything here is wrong, the host can claim and correct the page above.Model: gemini-2.5-pro · high confidence
- [01]The Data Engineering Show - Fame.sopodcasts.fame.so
- [02]The Data Engineering Show - Apple Podcastspodcasts.apple.com
- [03]About — Fireboltfirebolt.io
- [04][Vaccination 2021] How We Build Firebolt (Benjamin Wagner) - CMU Database Groupdb.cs.cmu.edu
- [05]The Data Engineering Show: Contact Information, Journalists, and Overview - Muck Rackmuckrack.com
- [06]Eldad Farkash - Co-Founder & CEO, Firebolt - Highperformrhighperformr.com
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