Summary
David Nies is a Big Data Engineer/Scientist with 15 years' experience building scalable, production-grade data pipelines and analytics platforms from his base in Freiburg, Germany. He currently applies his expertise at SICK after designing real-time and batch processing systems at ADITION where he worked extensively with Hadoop, Storm, Kafka, Parquet/Avro and other large-scale data technologies. Trained as a mathematician, he brings a rigorous, simulation-driven approach from earlier environmental modeling work to engineering problems, enabling precise handling of streaming telemetry and high-volume datasets. Comfortable across infrastructure and tooling layers, he focuses on stability, performance and deployability while staying eager to adopt new technologies. Colleagues describe him as a curious engineer who blends academic discipline with hands-on craftsmanship to turn complex data challenges into reliable production services.
15 years of coding experience
2 years of employment as a software developer
Diplom, Mathematik, Diplom, Mathematik at Albert-Ludwigs-Universität Freiburg im Breisgau
English, French