Hendrik Makait is a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, he works as an Open Source Engineer at Coiled maintaining and improving Dask and its distributed execution engine. His focus areas include P2P shuffling which allows shuffling large data at constant memory, and observability with Dask to help users understand and optimize their workloads.

Previously, he has worked on scalable data management for multimodal and unstructured sensor data, as well as data engineering for business intelligence. He worked on the design and implementation of a scalable query engine at SiaSearch (acquired by Scale AI), and later scaling the ingestion and querying capabilities of Scale Nucleus. Before that, we was a data engineer at Project A working companies ranging from pre-seed startups to established marketplaces with 500+MM USD valuations to design, implement, and improve their data analytics capabilities.

While doing his M.Sc in Computer Science at TU Berlin, he did research on data management with modern hardware at thea DIMA Group at TU Berlin and later at the DES Group at HPI. He wrote his thesis on rethinking message brokers to leverage remote direct memory access and persistent memory, and his research was awarded 2nd place in the Graduate Student category at the ACM SIGMOD 2020 Student Research Competition.


  • Large-Scale Data Systems

  • Distributed Computing

  • Machine Learning Systems

  • Open Source Software


  • M. Sc. in Computer Science, 2017 - 2020
    Technische Universität Berlin, Berlin, Germany

  • Visiting Undergraduate Student, 2014
    Harvard University, Cambridge, USA

  • Visiting Undergraduate Student, 2014
    Massachusetts Institute of Technology, Cambridge, USA

  • B. Sc. in Computer Science and Business Management, 2011 - 2015
    Nordakademie, Elmshorn, Germany