Vova Kolmakov
Principal Engineer at Huawei
Novosibirsk, Novosibirsk, Russia
Summary
🤩
Rockstar🎓
Top SchoolVova Kolmakov is a Principal Engineer with 10 years of hands-on experience building backend and data systems, currently at Huawei and an active Apache Hudi committer. He combines deep Java and Spring expertise with practical data engineering skills—Flink, Hadoop, Kafka and NiFi—to improve ETL pipelines and streaming integrations. His contributions to Hudi focus on Flink integration, duplicate-insert handling, and partitioning logic, reflecting a knack for making large-scale data pipelines more reliable and performant. Previously he led backend and ETL work at Beeline Russia and several software consultancies, and began his career in Lotus Notes/Domino development, which gave him a long-standing foundation in enterprise systems. Based in Novosibirsk with an applied mathematics background, he brings both rigorous problem-solving and pragmatic code-level optimizations to complex distributed systems.
10 years of coding experience
15 years of employment as a software developer
Engineer's degree, Applied Mathematics, Engineer's degree, Applied Mathematics at Новосибирский Государственный Технический Университет (НГТУ)
Английский
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (8)
javas10
big-data10
flink-sql10
apache-flink10
incremental-processing10
data-integration10
java10
data-engineering10
Programming languages (1)
Github contributions (5)
apache/hudi
Jun 2023 - Apr 2025
Upserts, Deletes And Incremental Processing on Big Data.
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:172 reviews, 134 PRs, 47 pushes in 1 year 9 months
Contributions summary:Vova primarily contributed to bug fixes, feature implementations, and refactoring efforts within the Hudi framework, specifically related to Flink integration. The user addressed issues in partition specification generation, improved the handling of duplicate inserts, and made code enhancements to optimize object creation and improve data pipeline performance. Additionally, the user's work encompassed configurations and functionalities related to supporting external systems and streamlining data operations.
stream-processingbigdatahudiincrementalapacheflink
wombatu-kun/hudi
Jun 2023 - Mar 2025
Upserts, Deletes And Incremental Processing on Big Data.
Contributions:2 PRs, 500 pushes, 88 branches in 1 year 9 months
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