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The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

Astronomer
The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI
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  • Inside Modern Data Infrastructure at Massdriver with Cory O’Daniel and Jake Ferriero
    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:Cory O’Danielhttps://www.linkedin.com/in/coryodaniel/Massdriver | LinkedInhttps://www.linkedin.com/company/massdriver/Massdriver | Websitehttps://www.massdriver.cloud/Jacob Ferrierohttps://www.linkedin.com/in/jacob-ferriero/Astronomerhttps://www.linkedin.com/company/astronomer/Apache Airflowhttps://airflow.apache.org/Prequelhttps://www.prequel.co/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.#AI #Automation #Airflow #MachineLearning
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  • The Future of Airflow Telemetry with Bolke de Bruin
    Telemetry has the potential to guide the future of Airflow, but only if it’s implemented transparently and with community trust. In this episode, we’re joined by Bolke de Bruin, Director at Metyis and a long-time Airflow PMC member. Bolke discusses how telemetry has been handled in the past, why it matters now and what it will take to get it right.Key Takeaways:(03:20) The role of foundations in establishing credibility and sustainability.(04:52) Why data collection is critical to open-source project direction.(07:24) Lessons learned from previous approaches to user data collection.(10:23) The current state of telemetry in the project.(10:53) Community trust as a prerequisite for technical implementation.(12:54) The importance of managing sensitive data within trusted ecosystems.(16:37) Ethical considerations in balancing participation and access.(18:45) Forward-looking ideas for improving workflow design and usability.Resources Mentioned:Bolke de Bruinhttps://www.linkedin.com/in/bolke/Metyis | LinkedInhttps://www.linkedin.com/company/metyis/Metyis | Websitehttp://www.metyis.comApache Airflowhttps://airflow.apache.org/Airflow Summithttps://airflowsummit.org/Airflow Dev Listhttps://lists.apache.org/[email protected]://www.astronomer.io/events/roadshow/london/ https://www.astronomer.io/events/roadshow/new-york/ https://www.astronomer.io/events/roadshow/sydney/ https://www.astronomer.io/events/roadshow/san-francisco/ https://www.astronomer.io/events/roadshow/chicago/ 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.#AI #Automation #Airflow #MachineLearning
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  • Transforming the Airflow UI for Cloudera’s Users with Shubham Raj
    Contributing to open-source projects can be daunting, but it can also unlock unexpected innovation. This episode showcases how one engineer’s journey with Apache Airflow led to impactful UI enhancements and infrastructure solutions at scale. Shubham Raj, Software Engineer II at Cloudera, shares how his team built a drag-and-drop DAG editor for non-coders, contributions which helped shape the Airflow 3.0 Ul and introduced features like external XCom control and bulk APls.Key Takeaways:(02:30) Day-to-day responsibilities building platforms that simplify orchestration.(05:27) Factors that make onboarding into large open-source projects accessible.(07:35) The value of improved user interfaces for task state visibility and control.(09:49) Enabling faster debugging by exposing internal data through APIs.(13:00) Balancing frontend design goals with backend functionality.(14:19) Creating workflow editors that lower the barrier to entry.(16:54) Supporting a variety of task types within a visual DAG builder.(19:32) Common infrastructure challenges faced by orchestration users.(20:37) Addressing dependency management across distributed environments.Resources Mentioned:Shubham Rajhttps://www.linkedin.com/in/shubhamrajofficial/Cloudera | LinkedInhttps://www.linkedin.com/company/cloudera/Cloudera | Websitehttps://www.cloudera.com/Apache Airflowhttps://airflow.apache.org/2023 Airflow Summithttps://airflowsummit.org/https://www.astronomer.io/events/roadshow/london/ https://www.astronomer.io/events/roadshow/new-york/ https://www.astronomer.io/events/roadshow/sydney/ https://www.astronomer.io/events/roadshow/san-francisco/ https://www.astronomer.io/events/roadshow/chicago/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.#AI #Automation #Airflow #MachineLearning
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  • Streamlining Thousands of Data Pipelines at Lyft with Yunhao Qing
    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 Yunhao Qing, Software Engineer at Lyft, about building a governed data-engineering platform powered by Airflow that balances flexibility, standardization and scale.Key Takeaways:(03:17) Supporting internal teams with a centralized orchestration platform.(04:54) Migrating to a managed service to reduce infrastructure overhead.(06:04) Embedding platform-level governance into custom components.(08:02) Consolidating and regulating the creation of custom code.(09:48) Identifying and correcting inefficient workflow patterns.(11:17) Replacing manual workarounds with native platform features.(14:32) Preparing teams for major version upgrades.(16:03) Leveraging asset-based scheduling for smarter triggers.(18:13) Envisioning GenAI and semantic search for future productivity.Resources Mentioned:Yunhao Qinghttps://www.linkedin.com/in/yunhao-qingLyft | LinkedInhttps://www.linkedin.com/company/lyft/Lyft | Websitehttps://www.lyft.com/Apache Airflowhttps://airflow.apache.org/Astronomerhttps://www.astronomer.io/Kuberneteshttps://kubernetes.io/https://www.astronomer.io/events/roadshow/london/ https://www.astronomer.io/events/roadshow/new-york/ https://www.astronomer.io/events/roadshow/sydney/ https://www.astronomer.io/events/roadshow/san-francisco/ https://www.astronomer.io/events/roadshow/chicago/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.#AI #Automation #Airflow #MachineLearning
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  • Transforming Customer Education in Data Engineering at Astronomer with Marc Lamberti
    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, Head of Customer Education at Astronomer, joins us to share his journey from Udemy instructor to driving education at Astronomer, and how he's helping over 100,000 learners demystify Airflow.Key Takeaways:(02:36) Early exposure to Airflow while addressing inefficiencies in data workflows.(04:10) Common barriers to implementing open source tools in enterprise settings.(06:18) The shift from part-time teaching to a full-time focus on Airflow education.(07:53) A modular, guided approach to structuring educational content.(09:57) The value of highlighting underused Airflow features for broader adoption.(12:35) Certifications as a method to assess readiness and uncover knowledge gaps.(13:25) Coverage of essential Airflow concepts in the Fundamentals exam.(16:07) The DAG Authoring exam’s emphasis on practical, advanced features.(20:08) A call for more visible integration of Airflow with AI workflows.Resources Mentioned:Marc Lambertihttps://www.linkedin.com/in/marclamberti/Astronomer | LinkedInhttps://www.linkedin.com/company/astronomer/Astronomer Academyhttps://academy.astronomer.io/Airflow Fundamentals Certificationhttps://www.astronomer.io/certification/DAG Authoring Certificationhttps://academy.astronomer.io/plan/astronomer-certification-dag-authoring-for-apache-airflow-examThe Complete Hands-On Introduction to Airflowhttps://www.udemy.com/course/the-complete-hands-on-course-to-master-apache-airflow/?utm_source=adwords&utm_medium=udemyads&utm_campaign=Search_DSA_Beta_Prof_la.EN_cc.ROW-English&campaigntype=Search&portfolio=ROW-English&language=EN&product=Course&test=&audience=DSA&topic=&priority=Beta&utm_content=deal4584&utm_term=_._ag_162511579404_._ad_696197165418_._kw__._de_c_._dm__._pl__._ti_dsa-1677053911088_._li_9061346_._pd__._&matchtype=&gad_source=1&gad_campaignid=21168154305&gbraid=0AAAAADROdO3MpljfP-gssiYSmDEPdhZV9&gclid=Cj0KCQjw097CBhDIARIsAJ3-nxdjZA6G5-Y0-akk6Huksy2PLb04t92J4iNfUSIbMdrSAla_tb-o2N8aArOeEALw_wcB&couponCode=PMNVD3025https://www.astronomer.io/events/roadshow/london/ https://www.astronomer.io/events/roadshow/new-york/ https://www.astronomer.io/events/roadshow/sydney/ https://www.astronomer.io/events/roadshow/san-francisco/ https://www.astronomer.io/events/roadshow/chicago/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.#AI #Automation #Airflow #MachineLearning
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About 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/
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