All Episodes
Data Engineering Podcast — 518 episodes · page 1 of 6
Reducing Data Debt with Agile Ledger Architecture
What Context Really Means in Data Engineering and AI
Specialized AI for Data Engineers: Inside Astronomer’s Otto
Why Multi-Agent Systems Need Shared State, Graph Semantics, and Governance
Building the Context Flywheel for AI Data Agents
Holding Kafka Right: Product-Friendly Streaming with TypeStream
Text to Data Products: Kaarvi’s End-to-End AI for Ingestion, Quality, and Dashboards
Scaling Graph Analytics Without ETL: Inside PuppyGraph’s Architecture
Maximizing GPU Utilization: Heterogeneous Pipelines with Ray and Kubernetes
The AI-First Data Engineer: 10–50x Productivity and What Changes Next
Treat Metering Like Finance: Building Data Platforms for Consumption Economics
Beyond the PDF: Rowan Cockett on Reproducible, Composable Science
Beyond Prompts: Practical Paths to Self‑Improving AI
Orion at Gravity: Trustworthy AI Analysts for the Enterprise
From Models to Momentum: Uniting Architects and Engineers with ER/Studio
From Data Models to Mind Models: Designing AI Memory at Scale
Prompt Management, Tracing, and Evals: The New Table Stakes for GenAI Ops
From Legacy to AI-Ready: How MongoDB AMP Accelerates Modernization
Branches, Diffs, and SQL: How Dolt Powers Agentic Workflows
Logical First, Physical Second: A Pragmatic Path to Trusted Data
Your Data, Your Lake: How Observe Uses Iceberg and Streaming ETL for Observability
Semantic Operators Meet Dataframes: Building Context for Agents with FENIC
Beyond Dashboards: How Data Teams Earn a Seat at the Table
Unfreezing The Data Lake: The Future-Proof File Format
From Context to Semantics: How Metadata Powers Agentic AI
From Data Engineering to AI Engineering: Where the Lines Blur
Malloy: Hierarchical Data, Semantic Models, and the Future of Analytics
Blurring Lines: Data, AI, and the New Playbook for Team Velocity
State, Scale, and Signals: Rethinking Orchestration with Durable Execution
The AI Data Paradox: High Trust in Models, Low Trust in Data
Bridging the AI–Data Gap: Collect, Curate, Serve
Beyond the Perimeter: Practical Patterns for Fine‑Grained Data Access
The True Costs of Legacy Systems: Technical Debt, Risk, and Exit Strategies
Context Engineering as a Discipline: Building Governed AI Analytics
The Data Model That Captures Your Business: Metric Trees Explained
From GPUs-as-a-Service to Workloads-as-a-Service: Flex AI’s Path to High-Utilization AI Infra
From RAG to Relational: How Agentic Patterns Are Reshaping Data Architecture
Duck Lake: Simplifying the Lakehouse Ecosystem
Aligning Business and Data: The Essential Role of Data Modeling
From Academia to Industry: Bridging Data Engineering Challenges
High Performance And Low Overhead Graphs With KuzuDB
Bridging Data and Decision-Making: AI's Role in Modern Analytics
From Bits to Tables: The Evolution of S3 Storage
Revolutionizing Python Notebooks with Marimo
Warehouse Native Incremental Data Processing With Dynamic Tables And Delayed View Semantics
Streamlining Data Pipelines with MCP Servers and Vector Engines
Foundational Data Engineering At Two Sigma
Enabling Agents In The Enterprise With A Platform Approach
Dagster's New Era: Modularizing Data Transformation in the Age of AI
AI and the Lakehouse: How Starburst is Pioneering New Workflows
Amazon S3: The Backbone of Modern Data Systems
Scaling Data Operations With Platform Engineering
From Data Discovery to AI: The Evolution of Semantic Layers
Balancing Off-the-Shelf and Custom Solutions in Data Engineering
StarRocks: Bridging Lakehouse and OLAP for High-Performance Analytics
Exploring NATS: A Multi-Paradigm Connectivity Layer for Distributed Applications
Advanced Lakehouse Management With The LakeKeeper Iceberg REST Catalog
Simplifying Data Pipelines with Durable Execution
Overcoming Redis Limitations: The Dragonfly DB Approach
Bringing AI Into The Inner Loop of Data Engineering With Ascend
Astronomer's Role in the Airflow Ecosystem: A Deep Dive with Pete DeJoy
Accelerated Computing in Modern Data Centers With Datapelago
The Future of Data Engineering: AI, LLMs, and Automation
Evolving Responsibilities in AI Data Management
CSVs Will Never Die And OneSchema Is Counting On It
Breaking Down Data Silos: AI and ML in Master Data Management
Building a Data Vision Board: A Guide to Strategic Planning
How Orchestration Impacts Data Platform Architecture
An Exploration Of The Impediments To Reusable Data Pipelines
The Art of Database Selection and Evolution
Bridging Code and UI in Data Orchestration with Kestra
Streaming Data Into The Lakehouse With Iceberg And Trino At Going
An Opinionated Look At End-to-end Code Only Analytical Workflows With Bruin
Feldera: Bridging Batch and Streaming with Incremental Computation
Accelerate Migration Of Your Data Warehouse with Datafold's AI Powered Migration Agent
Bring Vector Search And Storage To The Data Lake With Lance
The Role of Python in Shaping the Future of Data Platforms with DLT
Build Your Data Transformations Faster And Safer With SDF
Scaling Airbyte: Challenges and Milestones on the Road to 1.0
Enhancing Data Accessibility and Governance with Gravitino
The Evolution of DataOps: Insights from DataKitchen's CEO
Achieving Data Reliability: The Role of Data Contracts in Modern Data Management
How Generative AI Is Impacting Data Engineering Teams
The Role of Product Managers in Data-Centric Organizations
Neon: A Serverless And Developer Friendly Postgres
Improve Data Quality Through Engineering Rigor And Business Engagement With Synq
Stitching Together Enterprise Analytics With Microsoft Fabric
Being Data Driven At Stripe With Trino And Iceberg
X-Ray Vision For Your Flink Stream Processing With Datorios
Practical First Steps In Data Governance For Long Term Success
Data Migration Strategies For Large Scale Systems
Zenlytic Is Building You A Better Coworker With AI Agents
Release Management For Data Platform Services And Logic
Barking Up The Wrong GPTree: Building Better AI With A Cognitive Approach
Build Your Second Brain One Piece At A Time
Making Email Better With AI At Shortwave
Designing A Non-Relational Database Engine
Establish A Single Source Of Truth For Your Data Consumers With A Semantic Layer
Adding Anomaly Detection And Observability To Your dbt Projects Is Elementary
Ship Smarter Not Harder With Declarative And Collaborative Data Orchestration On Dagster+