The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI
Welcome to The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI— the podcast where we keep you up to date with insights and ideas propelling the Airflow community forward. Join us each week, as we explore the current state, future and potential of Airflow with leading thinkers in the community, and discover how best to leverage this workflow management system to meet the ever-evolving needs of data engineering and AI ecosystems. Podcast Webpage: https://www.astronomer.io/podcast/
Episodes
Managing data pipelines at scale is not just a technical challenge. It is also an organizational one. At Lyft, success means empowering dozens of teams to build with autonomy while enforcing governance and best practices across thousands of workflows.
In this episode, we speak with
Understanding the complexities of Apache Airflow can be daunting for newcomers and seasoned data engineers. But with the right guidance, mastering the tool becomes an achievable milestone.
In this episode, Marc Lamberti
The flexibility of Airflow plays a pivotal role in enabling decentralized data architectures and empowering cross-functional teams.
In this episode, we speak with Alberto Crespi, Data Architect at lastmin...
Innovation in orchestration is redefining how engineers approach both traditional ETL pipelines and emerging AI workloads. Understanding how to harness Airflow’s flexibility and observability is essential for teams navigating today’s evolving data landscape.
In this episode, Anu ...
Legacy architecture and AI workloads pose unique challenges at scale, especially in a global enterprise with complex data systems. In this episode, we explore strategies to proactively monitor and optimize pipelines while minimizing downstream failures.
Adonis Castillo Cordero, Senior A...
Building reliable data pipelines starts with maintaining strong data quality standards and creating efficient systems for auditing, publishing and monitoring. In this episode, we explore the real-world patterns and best practices for ensuring data pipelines stay accurate, scalable and trustworthy.
Creating consistency across data pipelines is critical for scaling engineering teams and ensuring long-term maintainability.
In this episode, Snir Israeli, Senior Data Engineer at Next Insurance, shares how enforcing coding standar...
Airflow’s adaptability is driving Tekmetric’s ability to unify complex data workflows, deliver accurate insights and support both internal operations and customer-facing services — all within a rapidly growing startup environment.
In this episode, Ipsa Trivedi, Lead Data Engineer at...
The Airflow 3.0 release marks a significant leap forward in modern data orchestration, introducing architectural upgrades that improve scalability, flexibility and long-term maintainability.
In this episode, we welcome Vikram Koka
The evolution of data orchestration at Instacart highlights the journey from fragmented systems to robust, standardized infrastructure. This transformation has enabled scalability, reliability and democratization of tools for diverse user personas.
In this episode, we’re joined by
Data orchestration at scale presents unique challenges, especially when aiming for flexibility and efficiency across cloud environments. Choosing the right tools and frameworks can make all the difference.
In this episode, Raviteja Tholupunoori, Senior Engineer at Deloitte ...
The 2025 State of Airflow report sheds light on how global users are adopting, evolving and innovating with Apache Airflow. With over 5,000 responses from 116 countries, the survey reveals critical insights into Airflows’ role in business operations, new use cases and what’s ahead for the community.
In this episode, Tamara Fin...
The orchestration layer is evolving into a critical component of the modern data stack. Understanding its role in DataOps is key to optimizing workflows, improving reliability and reducing complexity.
In this episode, Andy Byron
The security of open-source software is a growing concern, especially as dependencies and regulations become more complex, making it essential to understand how to manage software supply chains effectively.
In this episode, we sit down with Michael Winser, Co-Founder at Alpha-Omeg...
Machine learning is changing fast, and companies need better tools to handle AI workloads. The right infrastructure helps data scientists focus on solving problems instead of managing complex systems. In this episode, we talk with Savin Goyal, Co-Founder and CTO at Outerbounds, about b...
Keeping data pipelines reliable at scale requires more than just the right tools — it demands constant innovation. In this episode, Nick Bilozerov, Senior Data Engineer at Stripe, and Sharadh Krishnamurthy, Engineering Manager at Stri...
Turning complex datasets into meaningful analysis requires robust data infrastructure and seamless orchestration. In this episode, we’re joined by Jennifer Melot, Technical Lead at the Center for Security and Emerging Technology Read more
Data orchestration is evolving rapidly, with dynamic workflows becoming the cornerstone of modern data engineering. In this episode, we are joined by Samyak Jain, Senior Software Engineer - Big Data at 99acres.com....
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