Senior Data Engineer and Data Architect at Datumo, focused on building production-grade Data & AI solutions on Microsoft Azure.

My work is centered on making AI useful in real environments:

• designing data platforms based mainly on Azure and Databricks
• building MLOps foundations for repeatable delivery
• connecting data engineering with machine learning systems
• shaping architectures for edge, IoT, and data-centric AI workloads

I care about systems that are scalable, observable, maintainable, and ready for production.

if (data_quality && platform_reliability && repeatable_delivery) {
    ai_system = production_ready;
}

Principles:
- Design for observability, not just deployment
- Treat data contracts as part of the architecture
- Operationalize ML like any other critical software system
- Prefer systems that scale under real workloads, not demo conditions

Outside of architecture diagrams and delivery pipelines, I am drawn to things that are hands-on, iterative, and built with intent.

• Animal lover with a soft spot for real-world chaos over perfect lab conditions
• Gaming enthusiast, especially where systems, strategy, and immersion matter
• DIY hobbyist who enjoys building, fixing, and understanding how things work end to end
• Naturally interested in edge devices, connected systems, and technology that escapes the slide deck and reaches the physical world