Wojciech Indyk is an Engineer of Data Intensive Systems with 10+ years building large-scale distributed processing platforms using Spark, Hadoop, Flink and associated ecosystems like Kafka, HBase and Hive. He pairs deep engineering (Scala/Java, Python) with 9 years of data science work—specializing in time-series classification, imbalanced learning and recommendation systems—and has published eight papers on distributed graph processing including journal and ICDM contributions. His career spans research and product teams (Konica Minolta, Samsung R&D, Agora) where he designed high-availability data architectures, predictive maintenance and web-scale analytics, and he regularly speaks at big data meetups. An active open-source contributor to H2O.ai, Sparkling-water and Apache projects, he combines production-grade integration skills with a researcher’s rigor from machine learning summer schools in Kyoto and Plymouth. Comfortable with remote work and contract roles, he’s currently open to remote contract opportunities and brings both hands-on implementation and architectural guidance for massive data pipelines. An often-overlooked strength is his long-standing focus on scalable graph and BSR-pattern processing, bridging classic map-reduce insights with modern streaming systems.
10 years of coding experience
11 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Wrocław University of Science and Technology
for PhD students Computer Science Machine Learning, for PhD students Computer Science Machine Learning at Kyoto University
for PhD students International Summer School on Pattern Recognition, for PhD students International Summer School on Pattern Recognition at University of Plymouth
Contributions:23 pushes, 10 branches in 8 years 1 month
spark-mlapachebig-datasparkscala
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Wojciech Indyk - Engineer Of Data Intensive Systems