I design and build scalable data platforms, cloud systems, and AI-native engineering workflows.
A simplified view of how I think about production data systems.
The strongest parts of my portfolio are the systems I helped design, scale, and make reliable.
Technical lead for the next generation sDNA platform, architecting automated and configurable data pipelines and enabling onboarding across 20+ countries.
Scaled production data engineering across 20+ sources and international markets, with automation focused on reliability, onboarding, and data quality.
Engineered large-scale data pipelines and optimized Databricks Spark workloads, supporting predictive analytics on more than 5TB of monthly data.
My current focus is where modern data-platform engineering meets AI: reliable foundations, governed data, and workflows that make engineers and users more effective.
ETL/ELT, orchestration, modeling, governance, contracts, data products.
LLMs, MCP, RAG, LangGraph, semantic search, AI assistants, AI-to-BI.
Serverless, Kubernetes, containers, IaC, CI/CD, platform engineering.
Testing, observability, data quality monitors, contracts, automation.
From manufacturing and cybersecurity to global consumer data products, each role has added another layer to how I design systems.
I am a Principal Data Engineer based in Warsaw, focused on building reliable data platforms and helping teams move from pipelines toward reusable data products.
My background spans data engineering, software development, machine learning, cloud systems, and applied AI.
I studied Data Science and Business Analytics at the University of Warsaw, Computer Science at the Polish-Japanese Academy of Information Technology, and Electrical & Electronics Engineering at Boğaziçi University.
For professional conversations, collaboration, or technical discussions, the best places to find me are LinkedIn and GitHub.