Informed decision making for the Industry - data platform engineering

Industrial data platform engineering

Whether decision making is done by an AI or by a human agent, the first pillar to any successful implementation are clean and structured data.

You can watch a presentation of my work in this video during the last battery gigafactory summit in Berlin.

Modern industrial environments generate large volumes of data from production equipment, legacy and modern industrial protocols, business applications, quality systems, and operational processes. The challenge is not collecting data, but turning it into reliable information that supports daily operations, performance monitoring, and strategic decision making.

I design, build, and operate industrial data platforms that connect production systems with business intelligence and analytics tools. My expertise covers the full data lifecycle, including:

• Industrial data acquisition and integration (MQTT, OPC-UA, Modbus, custom interfaces, APIs)
• Data pipeline design and orchestration
• ETL/ELT workflows and data transformation
• Relational and time-series data management
• Data marts and KPI-oriented analytical models
• Production performance and productivity reporting
• Containerized application deployment and operation
• Identity and access management for data-driven applications
• Dashboarding and reporting platforms (Power BI, Grafana, custom applications)
• Data governance and single-source-of-truth architectures

My approach combines data engineering, software engineering, and industrial operations knowledge to deliver pragmatic, maintainable, and business-focused solutions. Whether the objective is production monitoring, operational excellence, traceability, quality management, or executive reporting, I help organizations create robust data platforms that provide trusted information where and when it is needed.

I firmly believe in sovereign architecture based on open source software.