The Analytics Engineering Podcast

Tristan talks with Russell Spitzer, a PMC member of Apache Iceberg and principal engineer at Snowflake, about the evolution of open table formats and the catalog layer. They dig into identity and access at the catalog layer and why consensus‑driven standards make interoperability possible.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.

Tristan talks with Lauren Anderson, Senior Director for Okta's Enterprise Data Platform. Lauren shares how identity sits at the center of two seismic shifts in data—AI agents and the open data lake—and why central governance and a shared semantic layer are critical. Lauren lays out how analytics engineers and data engineers should divide responsibilities as agents begin to write a growing share of analytical queries.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.

Snowflake VP of Product Management Chris Child joins Tristan Handy to unpack Snowflake's AI roadmap and what it means for data teams. They discuss the evolution from Snowpark to Cortex and Snowflake Intelligence, how to govern agents with row- and column-level controls, and why Snowflake is investing in Apache Iceberg and the Open Semantic Interchange initiative (dbt Labs recently open sourced MetricsFlow, the technology that powers the dbt Semantic Layer, to align with the goals of OSI). Chris also shares a vision for the next five years of data engineering: fewer bespoke pipelines, more standardization and semantics, and a bigger focus on business context and data products.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.

In this episode, Tristan Handy sits down with Chang She — a co-creator of Pandas and now CEO of LanceDB — to explore the convergence of analytics and AI engineering.
The team at LanceDB is rebuilding the data lake from the ground up with AI as a first principle, starting with a new AI-native file format called Lance. Tristan traces Chang's journey as one of the original contributors to the pandas library to building a new infrastructure layer for AI-native data. Learn why vector databases alone aren't enough, why agents require new architecture, and how LanceDB is building a AI lakehouse for the future.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.

Tristan talks with Mikkel Dengsøe, co-founder at SYNQ, to break down what agentic coding looks like in analytics engineering. Mikkel walks through a hands-on project using Cursor, the dbt MCP server, Omni's AI assistant, and Snowflake. They cover where agents shine (staging, unit tests, lineage-aware checks), where they're risky (BI chat for non-experts), and how observability is shifting from dashboards to root-cause explanations.
For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.
The Analytics Engineering Podcast is sponsored by dbt Labs.