Be Our Guest
Interested in being a guest on The Data Flowcast? Fill out the form and we will be in touch.
Managing modern data platforms means navigating a web of complex infrastructure, competing team needs and evolving security standards. For data teams to truly thrive, infrastructure must become both accessible and compliant without sacrificing velocity or reliability.
In this episode, we’re joined by Cory O’Daniel, CEO and Co-Founder at Massdriver, and Jacob Ferriero, Senior Software Engineer at Astronomer, to unpack what it takes to make data platform engineering scalable, sustainable and secure. They share lessons from years of experience working with DevOps, ML teams and platform engineers and discuss how Airflow fits into the orchestration layer of today’s data stacks.
Key Takeaways:
(03:27) Making infrastructure accessible without deep ops knowledge.
(07:23) Distinct personas and responsibilities across data teams.
(09:53) Infrastructure hurdles specific to ML workloads.
(11:13) Compliance and governance shaping platform design.
(13:27) Tooling mismatches between teams cause friction.
(15:13) Airflow’s orchestration role within broader system architecture.
(22:10) Creating reusable infrastructure patterns for consistency.
(24:13) Enabling secure access without slowing down development.
(26:55) Opportunities to improve Airflow with event-driven and reliability tooling.
Resources Mentioned:
Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.
Interested in being a guest on The Data Flowcast? Fill out the form and we will be in touch.
Try Astro today and get up to $500 in free credits during your 14-day trial.