Stijn De Haes
Partner at Data Minded
Leuven, Flemish Brabant, Belgium
Summary
🤩
Rockstar🎓
Top SchoolStijn De Haes is a seasoned data engineer and technology leader with nine years of experience building and stabilizing cloud-native data platforms from Leuven, Belgium. As Partner and Technical Lead at Data Minded, he combines hands-on engineering with delivery leadership, guiding teams on production data pipelines and orchestration. He has a proven track record as a backend and DevOps contributor to the widely used Apache Airflow project, where he improved Kubernetes deployment support and fixed stability issues in scheduling and Spark integration. Previously a tech lead at Conveyor and a senior engineer at Rombit, Stijn brings practical expertise across infrastructure, distributed systems, and observability. Trained in computer and electrical engineering at KU Leuven, he pairs solid academic foundations with real-world production experience. Notably, his open-source fixes target hard-to-diagnose runtime and scheduler problems, reflecting a bias for reliability in complex data workflows.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering (BEng), Computer Science, Electrical Engineering, Bachelor of Engineering (BEng), Computer Science, Electrical Engineering at KULeuven
English, Dutch, French
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (22)
kubernetes10
python10
data-engineering10
automation10
kubernetes-pods10
automations10
devops10
spark9
orchestra8
orchestration8
docker8
workflow-engine8
scheduler8
dockers8
testing7
Programming languages (19)
Github contributions (5)
apache/airflow
Jan 2019 - Jul 2024
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:10 reviews, 8 PRs, 39 comments in 5 years 6 months
Contributions summary:Stijn contributed to the Apache Airflow project by adding support for Kubernetes annotations and default resources for Kubernetes workers, enhancing the platform's deployment capabilities. They also addressed a bug related to Spark exit codes in the Spark submit operator, improving its integration. Moreover, the user fixed an issue where database sessions got stuck and another one related to a faulty scheduler state, improving the stability of Airflow.
monitorpythonschedulerapacheprogrammatically
stijndehaes/terraform-aws-eks
Mar 2019 - Jul 2021
A Terraform module to create an Elastic Kubernetes (EKS) cluster and associated worker instances on AWS.
Contributions:19 pushes, 2 branches in 2 years 4 months
instanceskubernetes-deploymentelasticeksworker
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