I like solving the problem behind the data.

My background combines engineering, operations, analytics and data engineering — which means I tend to look at data systems from both the technical and operational side.

I started my career working close to manufacturing operations and quality problems. That experience taught me to understand the process first: how work actually happens, where information breaks down and what decisions people are trying to make.

Today I apply that same thinking to data engineering. I build ingestion pipelines, transformation workflows, analytical models and reporting products that connect operational systems to useful information.

I'm especially interested in the space where engineering and analytics overlap — building systems that are technically reliable without losing sight of the people and processes they support.