about the authors

Julian de Ruiter is Field CTO Data + AI at Xebia Data, with a background in computer and life sciences and a PhD in computational cancer biology. He enjoys helping clients design and build AI solutions and platforms, as well as the teams that drive them. From this work, he has extensive experience in deploying and applying Airflow in production in diverse environments.

Ismael Cabral is a machine learning engineer and Airflow trainer with experience spanning Europe, the United States, Mexico, and South America, where he has worked with market-leading companies. He has vast experience implementing data pipelines and deploying machine learning models in production.

Kris Geusebroek is a data engineering consultant with extensive hands-on experience with Airflow at several clients and is the maintainer of Whirl (the open source repository for local testing with Airflow), where he is actively adding new examples based on new functionality and new technologies that integrate with Airflow.

Daniel van der Ende is a data engineer who started using Airflow in 2016. Since then, he has worked in many Airflow environments, both on premises and in the cloud. He has actively contributed to the Airflow project and to related projects such as Astronomer Cosmos.