Eugene Pustovit
Software Engineering Manager at Snowflake
Germany
Summary
🤩
Rockstar🎓
Top SchoolEugene Pustovit is a seasoned software engineering manager with 13 years of experience building and leading teams across distributed systems, ML engineering, and data platforms in Europe and the U.S. He has progressed from hands-on backend and database work—contributing to CrateDB’s SQL and IP validation features—to leading cross-functional teams at Zalando, Wayfair, and now Snowflake. Eugene excels at turning complex data and ML problems into production-grade services, recently overseeing catalog understanding, ML Ops, and visual similarity capabilities that power features like Search by Photo. Comfortable bridging low-level engineering and strategic product needs, he blends benchmarking and performance tuning experience with a track record of operationalizing ML and data pipelines. Based in Germany and trained in software engineering at Kyiv-Mohyla Academy, he brings a pragmatic, data-driven leadership style and a preference for measurable improvements under real-world load.
13 years of coding experience
14 years of employment as a software developer
Bachelor's degree Computer Software Engineering, Bachelor's degree Computer Software Engineering at National University of Kyiv-Mohyla Academy
English, Russian, Ukrainian, German
Github Skills (16)
javas10
databases10
sql10
java10
database10
cratedb10
amazon-elasticsearch9
elasticsearch-api9
testing9
aws-elasticsearch9
elasticsearchquery9
elasticsearch9
big-data8
dbms8
dbm8
Programming languages (5)
Github contributions (5)
crate/crate
Feb 2015 - Jun 2015
CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.
Role in this project:
Back-end Developer & Database Engineer
Back-end Developer & Database EngineerContributions:32 commits, 47 PRs, 47 pushes in 3 months
Contributions summary:Eugene contributed to the CrateDB codebase by implementing and testing features related to SQL query processing and data validation, specifically focusing on exception handling for count queries and IP address validation. They modified core components, including the `IpType` class for IP validation and the `ESQueryBuilder` for Elasticsearch query generation. Furthermore, the user added benchmark tests to assess table creation and alteration performance.
dbmscratedbon-toptime-seriesindustrial-iot
pustovit/crate
Feb 2015 - Mar 2015
Contributions:29 pushes, 20 branches in 1 month
elasticcratedata-storeelasticsearch
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