
Summary In this episode, I spoke with Keerti Kulkarni about the data and AI systems behind physical logistics automation at Amazon. She explained how her team supports dock-door operations across more than 100...


technology
Hosted by Tobias Macey · technology · EN
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.
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Signup to Generate a PitchThis 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.
Data Engineering Podcast is hosted by Tobias Macey. The show has published 520 episodes to date.
Recent episodes include "How Amazon Uses Telemetry and AI to Automate Physical Logistics" (20 October 2026, 50 minutes), "Reducing Data Debt with Agile Ledger Architecture" (24 September 2026, 50 minutes), and "What Context Really Means in Data Engineering and AI" (15 September 2026, 53 minutes).
Data Engineering Podcast publishes roughly every two weeks, with episodes averaging 54 minutes across 520 episodes.
Booking probability for Data Engineering Podcast is 38%, and the host is rated Selective on guests. Data Engineering Podcast requires a Pod Score of 80 or higher. Data Engineering Podcast's contact route on record: verified email.
The strongest fits for Data Engineering Podcast are IT Services & Software Development and Cloud, Data & Web Hosting. Data Engineering Podcast has a technology audience.
Tobias Macey hosts Data Engineering Podcast, a technology podcast with 520 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

Summary In this episode, I spoke with Keerti Kulkarni about the data and AI systems behind physical logistics automation at Amazon. She explained how her team supports dock-door operations across more than 100...

Summary In this episode Christopher Doidge talks about his Agile Ledger Architecture (ALA) approach to data warehousing and how it aims to reduce data debt while shortening the path from raw data to trustworthy business...

Summary In this episode Soham Azumdar, co-founder and CEO of Wisdom.ai, talks about what “context” really means in data engineering and AI systems. He explores why context has become such an overloaded term, spanning...

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...

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...

Episode #513
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...

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...

Summary In this episode Shravan Gunda, founder and CEO of Kaarvi AI, talks about building an AI-native, agent-driven data platform designed to eliminate the janitorial work that consumes most data teams. He...

Summary In this episode Weimo Liu, co‑founder of PuppyGraph, talks about the engineering behind their “zero-copy” graph querying engine for lakehouse and database sources. He explores how PuppyGraph lets you run Cypher...

Summary In this episode Robert Nishihara, co-founder of Anyscale and co-creator of Ray, talks about maximizing hardware utilization for AI and data-intensive workloads. He explores Ray’s evolution alongside Kubernetes...

Summary In this episode, I sit down with Gleb Mezhanskiy, CEO and co-founder of Datafold, to explore how agentic AI is reshaping data engineering. We unpack the leap from chat-assisted coding to truly agentic...

Summary In this episode Himant Goyal, Senior Product Manager at Salesforce, talks about how data platform investments enable reliable, accurate metering for consumption-based business models. Himant explains why...

Summary In this episode Rowan Cockett, co-founder and CEO of CurveNote and co-founder of the Continuous Science Foundation, talks about building data systems that make scientific research reproducible, reusable...

Summary In this episode Raj Shukla, CTO of SymphonyAI, explores what it really takes to build self‑improving AI systems that work in production. Raj unpacks how agentic systems interact with real-world...

Summary In this episode of the Data Engineering Podcast, Lucas Thelosen and Drew Gilson, co-founders of Gravity, discuss their vision for agentic analytics in the enterprise, enabled by semantic layers and broader...

Summary In this episode of the Data Engineering Podcast, Jamie Knowles (Product Director) and Ryan Hirsch (Product Marketing Manager) discuss the importance of enterprise data modeling with ER/Studio. They...

Summary In this episode of the Data Engineering Podcast, Vasilije "Vas" Markovich, founder of Cognee, discusses building agentic memory, a crucial aspect of artificial intelligence that enables systems to learn...

Summary In this episode of the Data Engineering Podcast, Aman Agarwal, creator of OpenLit, discusses the operational groundwork required to run LLM-powered applications reliably and cost-effectively. He highlights...

Summary In this episode, Shilpa Kolhar, SVP of Product and Engineering at MongoDB, discusses using MongoDB as a unified foundation for AI-driven and agentic applications. She explains how the Application Modernization...

Summary In this episode Tim Sehn, founder and CEO of DoltHub, talks about Dolt - the world’s first version‑controlled SQL database - and why Git‑style semantics belong at the heart of data systems and AI...
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