Summary
Dmitry Cherepov is a Solution Lead and seasoned data engineering specialist with 7+ years of hands-on experience building cloud-ready data platforms, ML Ops pipelines, and DevOps automation across finance, insurance, and retail. He has steered cloud migrations and anti-money-laundering hybrid-cloud designs at KBC, led small engineering teams, and promoted best practices in release management and code quality. Proficient in Python, Spark, SQL, Airflow and a broad AWS toolset, he pairs low-level pipeline craftsmanship with orchestration and CI/CD expertise (Jenkins, Teraflow). Dmitry’s background spans startup InsurTech builds to enterprise-scale transformations, giving him a pragmatic sense for both rapid prototyping and production hardening. Based in Mechelen, Belgium, he combines technical leadership with a continued focus on ML model operationalization—a capability honed at adidas and Accenture projects. Notably, his blend of Siebel/Oracle-era DevOps and modern cloud data engineering lends uncommon breadth to migration and modernization efforts.
2 years of coding experience
7 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at Bauman Moscow State Technical University
Master's degree Big Data Systems, Master's degree Big Data Systems at Higher School of Economics
Deep Learning Summer school, Deep Learning Summer school at Tsinghua University
Master's degree Information Systems Management, Master's degree Information Systems Management at FH Technikum Wien
English, Russian, German, French, Dutch