Summary
Egor Kotelnikov is a data engineer with 9 years’ experience building high-throughput batch and streaming pipelines and optimizing data lakehouse platforms. He has led a dataplatform team, hiring and mentoring engineers while delivering recommendation and retention models, and has hands-on expertise with Spark (Scala and PySpark), Kafka, Airflow, Hadoop/HDFS and S3. Currently focused on Spark Connect Server performance tuning, ML-driven data upload monitoring and observability with Grafana and PostgreSQL, he blends production optimization with practical ML applications. Trained as a physicist at MSU, he brings a rigorous, analytical approach to large-scale retail and telecom datasets, having worked with systems ingesting hundreds of millions of records per day.
9 years of coding experience
6 years of employment as a software developer
Master's degree, Physics, Master's degree, Physics at Московский Государственный Университет им. М.В. Ломоносова (МГУ)