Gezim Sejdiu
Chief Data Engineer
Bonn, North Rhine-Westphalia, Germany
Summary
🤩
Rockstar🎓
Top SchoolGezim Sejdiu is a Chief Data Engineer at DHL Data & AI and an Assistant Professor in Computer Science, bringing over a decade of experience building and scaling data platforms. He holds a PhD from the University of Bonn’s Smart Data Analytics group, with research spanning Semantic Web, Big Data and ML, and practical expertise in distributed engines like Apache Spark and Flink. At DHL he progressed from Senior Data Engineer to Chief Data Engineer, leading platform and deployment improvements that enable multi-version Spark configurations and more reliable build pipelines. As an educator he teaches MSc courses in Data Programming and Distributed Big Data Analytics, translating research into hands-on lab work used at Bonn and beyond. He combines academic rigor with production-first engineering, often contributing DevOps improvements to notable open-source Spark tooling. Colleagues describe him as a pragmatic problem-solver who bridges semantic research and industrial-scale data engineering.
10 years of coding experience
15 years of employment as a software developer
Master of Science (MSc) Computer Engineering, Master of Science (MSc) Computer Engineering at University of Prishtina – Faculty of Electrical and Computer EngineeringBachelor of Science (BSc) Computer Science, Bachelor of Science (BSc) Computer Science at University of Prishtina - Faculty of Mathematics and Natural SciencesPhD Semantic Web and Big Data, PhD Semantic Web and Big Data at The University of Bonn
Albanian, English
Stackoverflow
1reputation
0reached
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Github Skills (11)
apache-spark10
bash10
docker10
dockers10
build-automation10
kubernetes-pods9
kubernetes9
cicd8
scala7
maven7
python6
Programming languages (20)
Github contributions (5)
big-data-europe/docker-spark
Dec 2016 - Jul 2022
Apache Spark docker image
Role in this project:
DevOps Engineer
DevOps EngineerContributions:13 reviews, 117 commits, 42 PRs in 5 years 7 months
Contributions summary:Gezim focused on enhancing the build and deployment process for the Apache Spark docker image. They added support for various Spark versions, updated the build script, and integrated different Scala/Maven templates. They also worked on the history server configuration and simple python app. Their contributions ensured that the Docker image could support multiple Spark versions and configurations, enhancing usability and simplifying the build process.
spark-kubernetesdocker-imagedocker-sparkdockerapache
SANSA-Stack/Archived-SANSA-Examples
Dec 2017 - Jan 2020
Usage examples for the SANSA Stack
Contributions:12 releases, 8 commits, 14 PRs in 2 years 1 month
sansa
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