Alexander Verbitsky is a Data Processing Engineer with 13 years of software engineering experience, currently building data infrastructure at Goldman Sachs after leading geospatial data and MLOps efforts at OneSoil. He specializes in Python-driven data pipelines, satellite raster/vector processing, and deploying scalable infrastructure on AWS/GCP using Terraform/Pulumi, with strong production experience in Kafka, Airflow, Postgres and ML tooling like MLflow and DVC. His background spans low-level systems and web services—from Erlang backend work improving PostgreSQL client robustness to building real-time ML microservices for ETA and demand-supply modeling—reflecting a rare blend of systems reliability and applied ML. Based in Warsaw, he pairs a formal microelectronics education with hands-on cloud and GIS engineering, and contributes to open-source projects focused on stability and error-handling in database clients. Colleagues would describe him as pragmatic, detail-oriented, and comfortable taking ownership of end-to-end data lifecycles from ingestion to model inference.
13 years of coding experience
15 years of employment as a software developer
Bachelor of Engineering - BE Microelectronics, Bachelor of Engineering - BE Microelectronics at Belarusian State University of Informatics and Radioelectronics
Engineer's degree Microelectronics, Engineer's degree Microelectronics at Minsk State Higher Radioengineering College
Contributions:8 commits, 3 PRs, 5 comments in 9 months
Contributions summary:Alexander primarily focused on debugging and improving the error handling of the Erlang PostgreSQL client library. Their contributions involved fixing issues related to connection closures and unexpected crashes, ensuring the library's robustness. Additionally, the user made updates related to message language settings and merged upstream changes. This suggests a focus on improving stability and functionality.
Contributions:13 commits, 6 PRs, 13 pushes in 1 year
hexgridconfigurable
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