Podcast profile
Data Engineering Podcast
By Tobias Macey
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.
Latest episode
Why Multi-Agent Systems Need Shared State, Graph Semantics, and Governance
1 hr 2 min
- Cadence
- Weekly
- Typical length
- 57 min
- Latest release
- Aug 2, 2026
- Language
- EN
Topics
Engineering Practice
Building, testing, shipping, and operating technical systems.
Infrastructure & Operations
Cloud, networks, data platforms, reliability, and technical operations.
Formats
Interview
A host-led conversation with one or more guests.
Explainer & Deep Dive
Structured exploration of one subject in substantial depth.
Audience level
Advanced
Consistently technical, professional, or specialist in depth.
People behind the show
Current hosts
Listen from the original source
This directory never re-hosts or republishes podcast audio.
Official sources checked
Episode audio and show facts come from the checked-in refresh of the show’s public sources.
From the feed
Latest episodes
Data Engineering Podcast1 hr 2 min
Why Multi-Agent Systems Need Shared State, Graph Semantics, and Governance
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 specialized engine for traversal workloads, and how that perspective s
Data Engineering Podcast1 hr 1 min
Building the Context Flywheel for AI Data Agents
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 production, and how real performance depends on contextual intelligence: insti
Data Engineering Podcast50 min
Holding Kafka Right: Product-Friendly Streaming with TypeStream
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 unification, and document sync at scale highlighted both the strengths a
Data Engineering Podcast53 min
Text to Data Products: Kaarvi’s End-to-End AI for Ingestion, Quality, and Dashboards
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 explores Kaarvi’s multi-agent architecture that runs queries across seven LLMs in parallel for reliability, its s
Data Engineering Podcast54 min
Scaling Graph Analytics Without ETL: Inside PuppyGraph’s Architecture
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 and Gremlin traversals and graph algorithms directly on data in Iceberg, Delta, Hudi, Hive, and even
Data Engineering Podcast59 min
Maximizing GPU Utilization: Heterogeneous Pipelines with Ray and Kubernetes
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 and PyTorch, and why consolidation at these layers has enabled a new generation of complex, heterogene
Data Engineering Podcast59 min
The AI-First Data Engineer: 10–50x Productivity and What Changes Next
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 workflows where AI not only writes SQL and dbt models but also executes queries, debugs, runs tests, and ships
Data Engineering Podcast50 min
Treat Metering Like Finance: Building Data Platforms for Consumption Economics
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 consumption turns operations into a real-time optimization problem spanning metering, cost attribution, bill
Data Engineering Podcast43 min
Beyond the PDF: Rowan Cockett on Reproducible, Composable Science
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, and easier to communicate. He digs into the sociotechnical roots of the reproducibility crisis - from data i
Data Engineering Podcast1 hr 2 min
Beyond Prompts: Practical Paths to Self‑Improving AI
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 environments, the feedback loops that enable continuous learning, and why intelligent memory layers often provide the
Data Engineering Podcast1 hr 5 min
Orion at Gravity: Trustworthy AI Analysts for the Enterprise
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 context engineering. They share their journey from Looker and Google to building Orion, an AI analyst that
Data Engineering Podcast45 min
From Models to Momentum: Uniting Architects and Engineers with ER/Studio
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 highlight how clear, shared semantic models are a foundational discipline for modern data engineering, preventing
Data Engineering Podcast58 min
From Data Models to Mind Models: Designing AI Memory at Scale
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, adapt, and retain knowledge over time. He explains the concept of agentic memory, highlighting the importanc
Data Engineering Podcast51 min
Prompt Management, Tracing, and Evals: The New Table Stakes for GenAI Ops
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 common blind spots that teams face, including opaque model behavior, runaway token costs, and brittle prom
Data Engineering Podcast47 min
From Legacy to AI-Ready: How MongoDB AMP Accelerates Modernization
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 Platform (AMP) accelerates the transition from legacy relational systems to a document-first architect
Data Engineering Podcast57 min
Branches, Diffs, and SQL: How Dolt Powers Agentic Workflows
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 workflows. Tim explains how Dolt combines a MySQL/Postgres‑compatible interface with a novel storage engine built on
Data Engineering Podcast41 min
Logical First, Physical Second: A Pragmatic Path to Trusted Data
Summary In this episode of the Data Engineering Podcast Jamie Knowles, Product Director for ER/Studio, talks about data architecture and its importance in driving business meaning. He discusses how data architecture should start with business meaning, not just physical schemas, and explores the pitfalls of jumping stra
Data Engineering Podcast1 hr 12 min
Your Data, Your Lake: How Observe Uses Iceberg and Streaming ETL for Observability
Summary In this episode Jacob Leverich, cofounder and CTO of Observe, talks about applying lakehouse architectures to observability workloads. Jacob discusses Observe’s decision to leverage cloud-native warehousing and open table formats for scale and cost efficiency. He digs into the core pain points teams face with f
Data Engineering Podcast57 min
Semantic Operators Meet Dataframes: Building Context for Agents with FENIC
Summary In this episode Kostas Pardalis talks about Fenic - an open-source, PySpark-inspired dataframe engine designed to bring LLM-powered semantics into reliable data engineering workflows. Kostas shares why today’s data infrastructure assumptions (BI-first, expert-operated, CPU-bound) fall short for AI-era tasks tha
Data Engineering Podcast49 min
Beyond Dashboards: How Data Teams Earn a Seat at the Table
Summary In this episode Goutham Budati about his Data–Perspective–Action framework and how it empowers data teams to become true business partners. Gautham traces his path from automating Excel reports to leading high‑impact data organizations, then breaks down why technical excellence alone isn’t enough: teams must pa
Data Engineering Podcast59 min
Unfreezing The Data Lake: The Future-Proof File Format
Summary In this episode PhD researcher Xinyu Zeng talks about F3, the “future-proof file format” designed to address today’s hardware realities and evolving workloads. He digs into the limitations of Parquet and ORC - especially CPU-bound decoding, metadata overhead for wide-table projections, and poor random-access be
Data Engineering Podcast1 hr 6 min
From Context to Semantics: How Metadata Powers Agentic AI
Summary In this episode Suresh Srinivas and Sriharsha Chintalapani explore how metadata platforms are evolving from human-centric catalogs into the foundational context layer for AI and agentic systems. They discuss the origins and growth of OpenMetadata and Collate, why “context” is necessary but “semantics” is critic
Data Engineering Podcast27 min
From Data Engineering to AI Engineering: Where the Lines Blur
Summary In this solo episode of the Data Engineering Podcast, host Tobias Macey reflects on how AI has transformed the practice and pace of data engineering over time. Starting from its origins in the Hadoop and cloud warehouse era, he explores the discipline's evolution through ML engineering and MLOps to today's blen
Data Engineering Podcast59 min
Malloy: Hierarchical Data, Semantic Models, and the Future of Analytics
Summary In this episode Michael Toy, co-creator of Malloy, talks about rethinking how we work with data beyond SQL. Michael shares the origins of Malloy from his and Lloyd Tabb’s experience at Looker, why SQL’s mental model often fights human problem solving, and how Malloy aims to be a composable, maintainable languag
Data Engineering Podcast1 hr 1 min
Blurring Lines: Data, AI, and the New Playbook for Team Velocity
Summary In this crossover episode, Max Beauchemin explores how multiplayer, multi‑agent engineering is transforming the way individuals and teams build data and AI systems. He digs into the shifting boundary between data and AI engineering, the rise of “context as code,” and how just‑in‑time retrieval via MCP and CLIs