Grzegorz Kokosiński is a Senior Engineering Manager and co-founder with 11+ years building high-performance distributed database systems, currently leading engineering at Starburst. He combines hands-on backend development—significant contributions to Trino/Presto and Airlift—with leadership roles from tech lead to senior manager, shepherding enterprise-grade SQL-on-big-data products. His work spans deep systems engineering (Hive connector, blackhole connector, query-queue fixes) and production-grade reliability features like auth retries and discovery resilience. Based in Gdynia, Poland, he blends startup founder experience with long-term open-source stewardship as a Trino maintainer. Notably, his background includes GPU-accelerated analytics and storage-layer work at Netezza/IBM, giving him practical expertise across both hardware-accelerated algorithms and distributed query engines.
11 years of coding experience
17 years of employment as a software developer
MSc Computer Science, MSc Computer Science at Warsaw University of Technology
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
Role in this project:
Back-end Developer
Contributions:3289 reviews, 24 commits, 1404 PRs in 3 months
Contributions summary:Grzegorz's contributions focused on enhancing the codebase of the Trino distributed SQL query engine, particularly within the Hive connector. The commits addressed critical issues such as enumerating metadata objects, passing table owner information, and supporting for TEXTFILE formats. The contributions involved modifying existing Java classes, indicating the user's involvement in implementing features and addressing bugs.
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Contributions:2 reviews, 584 commits, 674 PRs in 4 years 3 months
Contributions summary:Grzegorz implemented the blackhole connector, which functions similarly to /dev/null, allowing for writes without actual data persistence and reads without data retrieval within the Presto distributed SQL query engine for big data. The user also fixed a race condition in the query queues, removing a check that was redundant and causing errors when multiple queries were submitted simultaneously. The user made updates to the code base by removing unnecessary synchronization in BlackHoleMetadata and made updates related to support for CTAS (Create Table As Select) with no data.
distributed-sqlquerybigdataquery-enginesql
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Grzegorz Kokosiński - Senior Engineering Manager at Starburst