Anton Okolnychyi

San Francisco, California, United States

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Summary

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Anton Okolnychyi is a software engineer with 11 years of experience specializing in scalable, fault-tolerant distributed systems and modern data lake architectures. Based in San Francisco, he is an Apache Iceberg committer and PMC member and an active Apache Spark contributor, helping make large-scale analytics engines more reliable and efficient. His work spans core backend improvements—implementing DELETE semantics, optimizing metadata and caching, and refactoring for newer Spark releases—to clearer, more usable Spark SQL documentation and examples. He has contributed to Delta Lake backend refactors and compatibility fixes, showing an eye for cross-project interoperability and long-term maintainability. Trained in computer science (Kyiv Polytechnic) and software systems engineering (RWTH Aachen), he combines rigorous academic grounding with hands-on open-source influence. Colleagues benefit from his knack for simplifying complex storage and query behaviors while shipping production-ready improvements in prominent projects like Spark and Iceberg.

11 years of coding experience

Master’s Degree, Software Systems Engineering, 1.3/1.0, Master’s Degree, Software Systems Engineering, 1.3/1.0 at RWTH Aachen University

Igor Sikorsky Kyiv Polytechnic Institute

English, Ukrainian

Stackoverflow

Stats

946reputation

267kreached

27answers

0questions

Badges

apache-spark

top-5%

Github Skills (27)

algorithm10

algorithms10

apache-spark10

spark10

delta-lake10

data-engineering10

big-data10

data-structure10

java10

scala10

javas10

sql10

apache-iceberg10

data-structures10

datastructures-algorithms10

Programming languages (4)

JavaScalaSCSSGo

Github contributions (5)

apache/iceberg

Dec 2018 - Jan 2023

Apache Iceberg

Role in this project:

Back-end Developer

Contributions:1 release, 5010 reviews, 322 commits in 4 years 1 month

Contributions summary:Anton's contributions focused on enhancing the core functionalities of Apache Iceberg, specifically within the context of its Spark integration. They implemented new features for data manipulation, such as adding rules and plans for DELETE operations, and also worked on optimizing aspects such as the caching of the Spark cache within procedures. Furthermore, the user contributed to improving the reliability and performance of metadata operations, including enhancements to the handling of file sequence numbers. The changes included refactoring and optimizing existing code to benefit from features in Spark 3.2 and 3.5.

apache-icebergapachebig-datadatastreamjava

apache/spark

Jan 2019 - Jan 2023

Apache Spark - A unified analytics engine for large-scale data processing

Role in this project:

Backend Developer

Contributions:661 reviews, 8 commits, 110 PRs in 4 years

Contributions summary:Anton's commits primarily involve updating and enhancing the Spark SQL programming guide and examples, specifically related to SQL programming, and user-defined aggregation functions. The user focused on clarifying and extending documentation related to aggregations, which included examples of both untyped and type-safe aggregation functions in Java and Scala, improving the clarity and utility of the guide. Their work also involved fixing existing documentation bugs, demonstrating a focus on improving the usability and correctness of the Spark SQL documentation.

analyticspythondata-processingsqlapache

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