Position: Data Engineer / MLOps
Category: Python
English level: fluent
Years of experience: 10


NDA - data warehouse and data science platform:
  Participated in the architecture of an on-premise data warehouse and data science platform, starting from defining technical specs for the bare metal machines.
 Created initial design of ETL migration from an in-house build system to open source
 Helped to set up development processes e.g.: code quality, the review process, on-boarding
 The main impact - I’ve initialized company “ETL”-mindset transformation, which helped to have much-complicated
analytics and insights generation.
 Impact: ​the whole ETL process had been improved, scaled up and automated, which gave the company the possibility
to scale up/down as much as it wanted. Performance for the running ETL processes increased in 2 times

NDA - machine learning productization system:
 Took lead in creating of the initial architecture
 Designed CI/CD pipeline to work with bare metal machines
 As a result of this project - the company started to use the on-line evaluation of the ml models instead of off-line one
 Impact​: Developed framework which helped to decrease ml model way to production from months to couple hours.
Insights Venture Partners - analytics platform:
 I played the main roles in system designs and was responsible for team building/hiring
 Helped to create ETL system which was generating meaningful insights for future investments

NDA - data aggregation:
 I played a key role in knowledge and project transfer from the other vendor, helped in code assessment and understanding of the definition of done for it.
 I was responsible for ETL processes revitalization - as a result I’ve increased speed and performance of the ETL into couple time