Kazuyuki Tanimura
Engineering Manager at Apple
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKazuyuki Tanimura is an engineering manager and seasoned software engineer with 15 years of experience building and hardening large-scale data systems, currently leading teams at Apple in Mountain View. He is an active open-source contributor and Apache DataFusion committer, ranking as the third-most prolific contributor to the DataFusion-Comet project and a repeat contributor to Apache Spark fixes around core data processing, memory optimizations, and test automation. With a Ph.D. in Computer Science from UC Irvine and prior roles across BloomReach and Synopsys, he blends deep research training with pragmatic engineering and production-grade testing practices. Known for improving Decimal handling, Parquet integration, and memory behaviors in Spark, he brings rare expertise at the intersection of distributed data engines and robust backend testing.
15 years of coding experience
6 years of employment as a software developer
Business Adminisration, Business Adminisration at University of OregonM.E. Computer Science, M.E. Computer Science at Waseda UniversityUniversity of California, Irvine
Japanese
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (13)
scala10
javas10
big-data10
spark10
java10
testing10
data-structure9
parquet9
data-structures9
algorithms8
sql8
websocket6
nodejs6
Programming languages (7)
Github contributions (5)
apache/spark
Aug 2021 - Apr 2022
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:139 reviews, 8 commits, 32 PRs in 7 months
Contributions summary:Kazuyuki primarily contributed to the Apache Spark project by fixing bugs and implementing improvements in core functionalities. Their work focused on addressing issues related to data processing and memory management, specifically related to Decimal calculations, Boolean handling, and memory optimizations. The user also added unit tests to ensure the accuracy and reliability of the implemented changes, especially in areas like Parquet file handling and data source integration. The contributions demonstrate expertise in core Spark components and testing methodologies.
analyticspythondata-processingsqlapache
kazuyukitanimura/stockexperiment
Sep 2015 - Dec 2017
Contributions:2 PRs, 993 pushes, 20 branches in 2 years 3 months
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