The engineering side of data.
I build data platforms: the systems that collect data, make it reliable and deliver it to products and AI agents. I work on the engineering side of data. I do not build dashboards or train models.
I have built data systems since 2016: Spark, Kafka and Cassandra at Honeywell, an event-driven IoT platform at Atos, and cloud and Databricks platforms at Datamole. I hired and grew two data engineering teams of 5 people each.
Today I lead Data Engineering at Datamole in Brno, and our move into agentic AI. Agents are part of how I build, so I know where they help and where they fail.
- Ingest: Everything you build depends on data that arrives complete and on time.
- Govern: People trust data only when its meaning, quality and access are clear.
- Act: Apps, reports and AI agents turn this data into decisions and actions.
Selected work.
A data product for public transport
Transport operators needed reliable data to plan and run their services. I led our adoption of Databricks and built a team of 5 data engineers. We adopted Lakeflow early, so the team could focus on what the operators needed from their data.
Predictive analytics for electron microscopes
Electron microscopes produce large amounts of data. I connected 50+ AWS services into one cloud-native platform for predictive analytics on this data, defined fully in code with CDK. I also hired and grew the first team of 5.
An IoT platform where milliseconds counted
I helped build one of the first full IoT platforms at Atos. The design was event-driven, with Akka and functional programming, for low latency, fault tolerance and scale.
Analytics for connected homes
I worked with Spark, Cassandra and Kafka behind Honeywell's connected-home platforms, before Spark was mainstream.
AWS and Databricks User Groups in Brno.
I help organize both groups and speak at them. Since February 2026, our speakers have come from AWS, SentinelOne, Sage, Kyndryl and E.ON.
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20 Oct 2026 · Databricks Brno #1
Databricks Brno meetup #1
- Setting up Lakeflow Connect Pipelines for Oracle and SQL Servers Juraj Paluba, Datamole
- 5 Layers Instead of 3: How We Expanded the Medallion Architecture for ML in Energy Michal Mec, E.ON
- Unity Catalog Hide and Seek: Personal Data Protection in Lakeflow Declarative Pipelines Speaker
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8 Oct 2026 · AWS Brno #4
AWS Brno Meetup #4
Clubco, Vlněna 5
- AWS Resilience Engineering George Palangattil Koshy, Kyndryl
- S3 Tables Gabriel Pajunk, Datamole
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29 Jul 2026 · AWS Brno #3
Summer AWS BBQ Meetup
Clubco, Vlněna 5
- Amazon S3 Vectors Speaker
- My Step Functions DAG Was a Lie: Going Agentic on 8,000 Photos Dmytro Hlotenko, Sage
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29 Apr 2026 · AWS Brno #2
AI Agents in Ops & Security
GEN Digital
- AWS DevOps Agent: Your Always-On Operations Teammate Jan Zelený, AWS
- AWS Security Agent: AI-Powered Security for the Speed of Development Akshay Kulkarni, SentinelOne
- AWS S3 Files Speaker
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5 Feb 2026 · AWS Brno #1
Building with GenAI & Autonomous Agents
GEN Digital, Vlněna 7
- The Curious Case of Generative AI Speaker
- Accelerating Software Development with Kiro and autonomous agent Sanjay Kashalkar, AWS
Building a product on top of data? Write to me.
Tell me what you are building and where your data comes from.
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