Building Event-Driven Data Pipelines With Airflow 3 at Astrafy with Andrea Bombino

Real-time data expectations are reshaping how modern data teams think about orchestration and dependencies. As event-driven architectures become more common, teams need to rethink how pipelines react to data changes, rather than schedules. In this episode, Andrea Bombino, Co-Founder and Head of Analytics Engineering at Astrafy, joins us to discuss how event-driven scheduling in Airflow is evolving and how Astrafy applies it to deliver faster, more responsive data pipelines. Key Takeaways: 00:00 Introduction. 02:02 Astrafy’s role in guiding clients across the modern data stack. 03:15 Strong DAG dependencies create challenges for time-based scheduling. 04:48 Event-driven pipelines respond to increasing real-time data demands. 05:30 Airflow 3 introduces native support for event-driven orchestration. 06:27 Sensor-based workflows reveal scalability and efficiency limitations. 11:32 Event-driven assets improve efficiency and pipeline elegance. 14:45 Governance and cross-instance coordination emerge as ongoing challenges. Resources Mentioned: Andrea Bombino https://www.linkedin.com/in/andrea-bombino/ Astrafy | LinkedIn https://www.linkedin.com/company/astrafy/ Astrafy | Website https://www.astrafy.io Apache Airflow https://airflow.apache.org/ Google Cloud https://cloud.google.com/ Google Pub/Sub https://cloud.google.com/pubsub Google BigQuery https://cloud.google.com/bigquery 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