Sergei Lilichenko
Cloud Solutions Architect at Google
Orinda, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSergei Lilichenko is a Cloud Solutions Architect at Google with over six years of focused experience in cloud-native architectures and a long history of designing high-availability, secure payment and data platforms. He led core API and platform development for Zelle—delivering a production-grade, patent-backed payments platform with zero P0/P1 incidents—and has built and led teams from startup to enterprise scale. Prior to Google he founded and ran a consulting and recruitment firm, giving him a rare blend of executive, technical hiring and client-facing delivery skills. At OneMarket and in his current role he has hands-on experience with GCP services such as Kubernetes Engine, Pub/Sub and Spanner, and contributes to Apache Beam by improving BigQueryIO and ordered sequence processing. Based in Orinda, CA, he pairs deep backend engineering chops with practical operational discipline, favoring measurable reliability and performance gains. His background suggests a pragmatic architect who moves fluidly between code, infrastructure and organizational execution.
6 years of coding experience
23 years of employment as a software developer
MS, Computer Science, MS, Computer Science at Kiev Politechnic
Github Skills (11)
javas10
bigquery10
data-pipelines10
data-pipeline10
apache-beam10
java10
streaming9
batching9
batch9
sql8
go4
Programming languages (4)
Github contributions (5)
apache/beam
Dec 2022 - Dec 2022
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:51 reviews, 2 commits, 6 PRs in 1 day
Contributions summary:Sergei primarily focused on improving the BigQueryIO connector and the "ordered" extension within the Apache Beam Java SDK. They addressed integer conversion issues in the BigQueryIO's Storage Write API, improving error messages and overall performance. Furthermore, the user implemented global sequence processing features within the "ordered" extension, including accumulator optimizations, timer logic refinements, and various bug fixes. These efforts improve the data processing capabilities of the Apache Beam framework.
golangpythonstreaming-databeambatch
slilichenko/beam
Nov 2022 - Jan 2025
Apache Beam is a unified programming model for Batch and Streaming data processing.
Contributions:76 pushes, 4 branches in 2 years 2 months
stream-processingstreaming-databeambatchdata-processing
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