Auro Mohanty is a data engineer with a decade of experience applying physics-grade rigor to data infrastructure and analytics. He combines a PhD in elementary particle physics and hands-on research at CERN with production engineering skills building feature stores, data pipelines, and Python packages across Databricks, Airflow, GCP, and Kubernetes. At Eneco he focuses on forecasting energy demand for sustainability, while prior roles at TRKKN and Annalect involved modernizing clients’ data platforms and migrating pipelines to cloud-native architectures. His open-source contributions include backend work on the ALICE analysis repository, translating domain-specific physics analyses into maintainable code—an unusual bridge between high-energy physics and commercial data engineering. Known for shipping practical CI/CD and dbt transformations as well as migrating services (Quarkus to FastAPI), he excels at turning complex scientific problems into reliable production systems. Based in Utrecht, he brings deep analytical thinking, meticulous testing habits, and a penchant for infrastructure that scales.
10 years of coding experience
8 years of employment as a software developer
D.A.V. Public School, Chandrasekharpur
Doctor of Philosophy - PhD Elementary Particle Physics, Doctor of Philosophy - PhD Elementary Particle Physics at Utrecht University
Bachelor and Master of Science (5 Year Integrated MSc) Physics, Bachelor and Master of Science (5 Year Integrated MSc) Physics at National Institute of Technology Rourkela
Contributions:30 commits, 14 PRs, 8 comments in 1 year 4 months
Contributions summary:Auro's commits focus on migrating code from the `PWGJE` to `PWGHF` directory, specifically within the context of charm-jet correlations and D meson analysis. They modified and updated the `AliAnalysisTaskDJetCorrelations` task and related macros. The changes include adjustments to analysis tasks, creation and connection of containers for input/output.
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