Kasia Findeisen is a seasoned backend software engineer with 17 years of experience, based in Warsaw, Poland, specializing in distributed SQL engines and performance-critical server-side code. She is an active open-source contributor to high-profile projects like Trino (formerly PrestoSQL) and Presto, where her work on window functions, table function invocation, and date/time utilities improved functionality and query performance. Her contributions also include robust fixes and tests for core libraries such as Airlift’s TDigest, demonstrating attention to numerical correctness and edge-case behavior. Known for pragmatic refactoring and performance-minded enhancements, she brings deep expertise in query engine internals and a track record of pushing subtle, correctness-focused improvements that have real impact on large-scale data processing.
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:916 reviews, 36 commits, 374 PRs in 5 months
Contributions summary:Kasia made several code contributions focused on optimizing the core functionality of the Trino project. Their work involved refactoring and improving the code related to window functions, table function invocation, and the processing of row pattern matching. These efforts resulted in enhancements, such as improved performance and the support of new specifications. The contributions were targeted towards a critical area for Trino's functionality.
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Contributions:5 commits, 3 PRs, 9 comments in 8 months
Contributions summary:Kasia primarily contributed to the Presto distributed SQL query engine by adding new functionalities and fixing existing issues. They implemented a millisecond function to extract the millisecond of the second from various data types, including timestamps, times, and intervals, and added tests to support this. They also addressed a typo in a variable name and introduced a new rule for pushing limits through outer joins to optimize query execution. Their work focused on enhancing the engine's date and time function capabilities.
distributed-sqlquerybigdataquery-enginesql
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