Embracing Data Mesh and SQL Sensors for Scalable Workflows at lastminute.com with Alberto Crespi
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 Airfl...
The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI · The Data Flowcast
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Show Notes
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:
https://www.linkedin.com/in/crespialberto/
lastminute.com | Website
https://lastminute.com
https://airflow.apache.org/
https://www.getdbt.com/
https://github.com/astronomer/astronomer-cosmos
https://slack.com/
https://kubernetes.io/
https://www.atlassian.com/software/confluence
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/
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#AI #Automation #Airflow #MachineLearning