Daniel is a Data Engineer at Dawn, focused on building scalable data systems and applications that transform complex datasets into actionable insights.

I’ve always been drawn to complex systems, especially the kind that look chaotic on the surface but reveal structure once you dig into the data. At Dawn, I build the data foundation & workflows for our AI products including Rolodex. VC is an industry that doesn’t typically embrace software and data. The enthusiasm at Dawn is unique - it is rewarding to not just build cutting edge solutions, but see them used daily.

Before Dawn, I spent several years working deeply with real estate and geospatial data, building large-scale pipelines and data platforms. That experience shaped how I think about data: most valuable datasets are messy, incomplete and constantly changing, and the real challenge is turning that into something consistent and trustworthy.

What I enjoy most is bridging the gap between technical complexity and usability. The goal isn’t just to build robust systems, but to make data feel intuitive and actionable for the people using it.

Outside of work, I spend most of my time training Brazilian Jiu-Jitsu, painting Warhammer, being outdoors with my dog, or diving into side projects around data and web applications.

Before joining Dawn, Daniel worked as a Backend Engineer at a full-service provider for e-commerce, a Full-Stack Developer at a media and communication service provider, and a Data Engineer at PREA, a data-driven real estate company.

Daniel holds a Bachelor’s degree in Computer Engineering from the Berliner Hochschule für Technik in Berlin.