Jorrick Sleijster is a Data Platform Engineer with 11 years of experience building scalable, production-grade data infrastructure and ETL pipelines. Based in Eindhoven, he helps run one of the world’s largest Apache Airflow deployments at Adyen, contributing upstream fixes and UI improvements to the Airflow project. He combines backend, DevOps and CI/CD expertise to streamline developer experience, Kafka pipelines, permissions management and local dev environments for ML and reporting workloads. Prior roles include data engineering at Schiphol where he deployed Kubernetes-backed APIs and Cassandra/CosmosDB stores for predictive models. A creator of handy open-source tools (iCal-library, macOS-notifications) and an active Airflow contributor, he pairs a formal Computer Science education (cum laude MS) with a lifelong curiosity for how technology works. His background in organized team leadership and sports coaching gives him a practical edge in planning, communication and delivering reliable systems under real-world constraints.
11 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Computer Science, Cum laude, Master of Science - MS, Computer Science, Cum laude at Eindhoven University of Technology
The secondary education, Pre-university education (VWO), Science and Engineering (Natuur en Techniek), The secondary education, Pre-university education (VWO), Science and Engineering (Natuur en Techniek) at Connect College
Bachelor of Software Sience, Software Sience, 7.4/10, Bachelor of Software Sience, Software Sience, 7.4/10 at Technische Universiteit Eindhoven
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end Developer & DevOps Engineer
Contributions:79 reviews, 31 PRs, 221 comments in 3 years 9 months
Contributions summary:Jorrick primarily contributed to bug fixes and enhancements within the Apache Airflow codebase. Their work included resolving issues related to the CeleryExecutor, task instance adoption, and DagRun state transitions. Furthermore, the user addressed UI inconsistencies and implemented new features, specifically adding a queue button to the DagRun interface. The user also made changes to improve the UI and documentation.
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