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 lastminute.com, who shares how his team scales Airflow across 12 teams while supporting both vertical and horizontal structures under a data mesh approach.

Key Takeaways:

(02:17) Defining responsibilities within data architecture teams.

(04:15) Consolidating multiple orchestrators into a single solution.

(07:00) Scaling Airflow environments with shared infrastructure and DevOps practices.

(10:59) Managing dependencies and readiness using SQL sensors.

(14:23) Enhancing visibility and response through Slack-integrated monitoring.

(19:28) Extending Airflow’s flexibility to run legacy systems.

(22:28) Integrating transformation tools into orchestrated pipelines.

(25:54) Enabling non-engineers to contribute to pipeline development.

(27:33) Fostering adoption through collaboration and communication.

Resources Mentioned:

Alberto Crespi

https://www.linkedin.com/in/crespialberto/

lastminute.com | Website

https://lastminute.com

Apache Airflow

https://airflow.apache.org/

dbt Labs

https://www.getdbt.com/

Astronomer Cosmos

https://github.com/astronomer/astronomer-cosmos

GitLabSlack

https://slack.com/

Kubernetes

https://kubernetes.io/

Confluence

https://www.atlassian.com/software/confluence

Slack

https://slack.com/

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