I’m a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, I work as a Data Engineer at SiaSearch, where we create a data management platform for unstructured sensor data. I am involved in most of our backend and data infrastructure, from data ingestion, over data management and cataloging, to building a scalable query engine and backend.

Previously, I completed my M.Sc. in Computer Science at TU Berlin with a focus on databases, large-scale data processing, and machine learning. During this time, I worked as a student researcher at the DIMA Group at TU Berlin and later at the DES Group at HPI. My thesis was on rethinking message brokers to leverage remote direct memory access and persistent memory, and part of this work was awarded 2nd place in the Graduate Student category at the ACM SIGMOD 2020 Student Research Competition. Even before my studies, I was a data scientist/engineer at Project A Ventures where I designed, implemented, and extended data warehouses, large data processing pipelines as well as data products built on top of those. I collaborated with startups in very different stages, ranging from pre-seed to established companies with a 500+MM USD valuation.

Feel free to reach out to me if you work on a compelling idea, company or open-source project in the space of large-scale data management and machine learning, or just want to have chat!