Lessons in Data Engineering: Scaling, AI, and Open Source with Sandy Ryza
Episode 111 of the Prodity: Product by Design podcast, hosted by Kyle Evans, titled "Lessons in Data Engineering: Scaling, AI, and Open Source with Sandy Ryza" was published on February 7, 2025 and runs 46 minutes.
February 7, 2025 ·46m · Prodity: Product by Design
Summary
In this episode of Product by Design, Kyle chats with Sandy Ryza, lead engineer on the Dagster project, author, and thought leader in data engineering. Sandy shares his journey through the world of data—from building big data tools at Cloudera to working as a data scientist, product manager, and engineer—and how those experiences led him to help create Dagster, an open-source data orchestration platform.We discuss:The evolution of data engineering and the growing complexity of modern data pipelines.The role of AI and unstructured data in shaping the future of data platforms.How organizations should think about data platforms to avoid costly rework.Best practices for managing data complexity using software engineering principles.The future of open-source tools in data infrastructure and the push toward interoperability.Sandy RyzaSandy is a lead engineer, author, and thought leader in the domain of data engineering. Sandy co-wrote “Advanced Analytics with PySpark” and “Advanced Analytics with Spark”. He led ML and data science teams at Cloudera, Remix, Clover Health, and KeepTruckin.Sandy is currently the lead engineer on the Dagster project, an open-source data orchestration platform used in MLOps, data science, IOT and analytics. Sandy is a regular speaker at data engineering and ML conferences.Links from the Show:Twitter: @s_RYZDagster: dagster.ioBook: Advanced Analytics with Spark – O'ReillyPodcast Recommendation: Empire (British Empire & Ottoman Empire history)Books Sandy is Reading: The Shortest History of India, The Sun Also Rises, Werner Herzog’s AutobiographyMore by Kyle:Follow Prodity on Twitter and TikTokFollow Kyle on Twitter and TikTokSign up for the Prodity Newsletter for more updates.Kyle's writing on MediumProdity on MediumLike our podcast, consider Buying Us a Coffee or supporting us on Patreon
Episode Description
In this episode of Product by Design, Kyle chats with Sandy Ryza, lead engineer on the Dagster project, author, and thought leader in data engineering. Sandy shares his journey through the world of data—from building big data tools at Cloudera to working as a data scientist, product manager, and engineer—and how those experiences led him to help create Dagster, an open-source data orchestration platform.
We discuss:
- The evolution of data engineering and the growing complexity of modern data pipelines.
- The role of AI and unstructured data in shaping the future of data platforms.
- How organizations should think about data platforms to avoid costly rework.
- Best practices for managing data complexity using software engineering principles.
- The future of open-source tools in data infrastructure and the push toward interoperability.
Sandy Ryza
Sandy is a lead engineer, author, and thought leader in the domain of data engineering. Sandy co-wrote “Advanced Analytics with PySpark” and “Advanced Analytics with Spark”. He led ML and data science teams at Cloudera, Remix, Clover Health, and KeepTruckin.
Sandy is currently the lead engineer on the Dagster project, an open-source data orchestration platform used in MLOps, data science, IOT and analytics. Sandy is a regular speaker at data engineering and ML conferences.
Links from the Show:
Twitter: @s_RYZ
Dagster: dagster.io
Book: Advanced Analytics with Spark – O'Reilly
Podcast Recommendation: Empire (British Empire & Ottoman Empire history)
Books Sandy is Reading: The Shortest History of India, The Sun Also Rises, Werner Herzog’s Autobiography
More by Kyle:
Follow Prodity on Twitter and TikTok
Follow Kyle on Twitter and TikTok
Sign up for the Prodity Newsletter for more updates.
Prodity on Medium
Like our podcast, consider Buying Us a Coffee or supporting us on Patreon
Similar Episodes
Apr 11, 2026 ·2m
Apr 11, 2026 ·8m
Apr 11, 2026 ·18m
Apr 11, 2026 ·18m
Apr 11, 2026 ·26m
Apr 11, 2026 ·19m