Sergii Zhevzhyk is a Software Development Engineer based in Germany with 11 years of experience building and optimizing backend systems. Currently at Amazon since 2020, he applies deep expertise in refactoring, performance tuning and reliable IO handling to large-scale, distributed codebases. An active open-source contributor, Sergii has improved maintainability and efficiency in prominent projects such as Apache BookKeeper and Apache Pulsar, and fixed subtle document-formatting bugs in the DocX .NET library, often adding unit tests to prevent regressions. He specializes in converting iterative patterns to bulk operations and modernizing Java code with lambdas and cleaner logging, yielding measurable stability and speedups. Trained as a computer engineer (BSc/MSc), he combines academic grounding with a pragmatic focus on readable, testable code for production systems. A behind-the-scenes detail: he gravitates toward surgical refactors that reduce allocation overhead and simplify complex I/O paths.
11 years of coding experience
Bachelor, Computer Engineering, Bachelor, Computer Engineering at Donetsk National Technical University
Fast and easy to use .NET library that creates or modifies Microsoft Word files without installing Word.
Role in this project:
Back-end Developer
Contributions:7 commits, 4 PRs in 8 months
Contributions summary:Sergii primarily contributed to fixing bugs and implementing features related to table manipulation and paragraph formatting within the .NET DocX library. They addressed issues such as incorrect column width settings, font size changes, and the implementation of cell margins. The user also wrote unit tests to verify these changes, ensuring the library's functionality and stability. Their work directly impacts the library's core functionalities for document generation.
Apache Pulsar - distributed pub-sub messaging system
Role in this project:
Back-end Developer
Contributions:2 reviews, 63 commits, 53 PRs in 1 year 1 month
Contributions summary:Sergii contributed to the `pulsar-log4j-appender` project by cleaning up tests and improving code structure, addressing issue #4681. The user also worked on the Presto module by cleaning up tests and optimizing the code, specifically the schema creation and conversion of functions to lambdas. Moreover, the user converted anonymous classes to lambda expressions in multiple files across various modules.
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