Kerwin Zhang
IT Developer-APP at Home Credit China
Hedong District, Tianjin, China
Summary
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Rockstar🎓
Top SchoolKerwin Zhang is an IT Developer with around three years of focused software engineering experience and a decade-plus background in system development and process automation across manufacturing and IT services. Based in Tianjin, he currently builds application-level solutions at Home Credit China and previously delivered system development work for Cognizant and Xerox. Kerwin contributes to high-performance open-source big data tooling—adding columnar shuffle support and dictionary encoding to the Apache Celeborn Spark integration—demonstrating a practical strength in optimizing distributed data transfer and serialization. He holds a Master’s in Engineering Management from Tianjin Nankai University and a bachelor’s in Computer Technology, blending technical depth with process-oriented thinking. Practical, performance-minded, and cross-domain experienced, he brings both legacy systems insight and modern big-data engineering skills to complex integration challenges.
3 years of coding experience
3 years of employment as a software developer
Master of Engineering Management, Engineering Management, Master of Engineering Management, Engineering Management at Tianjin Nankai Universitybachelor of science, Computer Technology, bachelor of science, Computer Technology at Tianjin University of Technology
Chinese, English
Stackoverflow
11reputation
177reached
0answers
1question
Github Skills (10)
scala10
javas10
big-data10
data-serialization10
spark10
shuffle10
java10
serialization10
code-generation9
android6
Programming languages (3)
Github contributions (5)
apache/celeborn
Sep 2022 - Nov 2022
Apache Celeborn is an elastic and high-performance service for shuffle and spilled data.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:42 reviews, 23 commits, 55 PRs in 2 months
Contributions summary:Kerwin contributed to the Apache Celeborn project by implementing and improving columnar shuffle functionality within the Spark integration. Their work included adding support for columnar shuffle in the shuffle writer, reader, and serializer components. The user also added features like dictionary encoding to enhance performance and optimize data transfer. These changes aimed to improve data processing efficiency and optimize shuffle operations within a big data environment.
bigdataaccumuloparquetelasticconnector
kerwin-zk/gluten
Jul 2023 - Apr 2025
Gluten: Plugin to Double SparkSQL's Performance
Contributions:358 pushes, 53 branches in 1 year 8 months
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