Dmitry Akatov is a machine learning engineer with 11 years of software development and data engineering experience, currently focusing on ML work in the Netherlands. He has designed and led scalable data platforms and real-time pipelines—from pg→Debezium→Kafka ingestion to analytical DWHs—and built fault-tolerant Airflow-based orchestration in Kubernetes and cloud environments. Dmitry combines hands-on engineering (Spark/Flink ETL, Scala, Python) with infrastructure and functional-programming sensibilities, having implemented monorepo CI/CD, k8s deployments, and observability for cross-functional teams. He has managed multiple data engineering teams and driven company-wide data foundation efforts that became single sources of truth for marketing and sales analytics. Comfortable across the stack, he brings an unusual blend of microelectronics training and pragmatic platform-building that helps bridge low-level systems thinking with high-level ML delivery.
11 years of coding experience
12 years of employment as a software developer
Engineer's degree Microelectronics and solid-state electronics, Engineer's degree Microelectronics and solid-state electronics at Moscow Power Engineering Institute (Technical University)
Contributions:1 PR, 218 pushes, 15 branches in 10 months
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Dmitry Akatov - Machine Learning Engineer at AB Quant BV