Naman Rastogi
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolNaman Rastogi is a software engineer and researcher with 11 years of experience building data-driven web and backend systems, currently based in the San Francisco Bay Area and interning at Starteryou. He combines full-stack skills (React, Node.js, PostgreSQL) with cloud-native tooling—designing Kubernetes services for field-level encryption and automating deployments with Terraform—to deliver scalable, production-ready features that cut onboarding time by 35%. His research at the University of Utah applied large-scale social computing techniques (Dask, BERTopic) to categorize 300M+ social posts and surface temporal and thematic patterns, work that has been presented at ACM GROUP and submitted to ACM CSCW. An active open-source contributor to Apache CarbonData, he has improved concurrent reads, performance of the storage engine, and key compaction and loading workflows—demonstrating a focus on storage optimization and data ingestion. Equally comfortable prototyping ML models and visualization dashboards, he blends rigorous research methods with pragmatic engineering to turn complex data into actionable products.
11 years of coding experience
3 years of employment as a software developer
The University of Utah10th, 10th at Delhi Public School Patna12th PCM, 12th PCM at B.D. Public SchoolBachelor of Technology - BTech Data Science, Bachelor of Technology - BTech Data Science at Vellore Institute of TechnologyVidyamandir Classes Patna
Github Skills (13)
data-storage10
javas10
data-loading10
big-data10
performance-optimization10
java10
data-engineering10
hadoop9
scala9
filesystem9
spark9
data-structures8
data-structure8
Programming languages (3)
Github contributions (5)
apache/carbondata
Oct 2018 - Jun 2019
High performance data store solution
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:34 commits, 23 PRs, 105 comments in 7 months
Contributions summary:Naman primarily contributed to improving the Apache CarbonData storage engine's functionality. Their work includes adding concurrent reading capabilities through the SDK, removing unnecessary configurations, and improving build times for the CarbonReader builder. They also implemented features like load-level sort scope configurations and enhancements to compaction processes, indicating a focus on data loading, performance, and storage optimization. Further contributions include bug fixes related to table renaming and pre-aggregate datamap creation failures, as well as providing the DDL to drop cache for a table.
carbondatadata-formatdata-storeapachebig-data
pmkalshetti/object_detection_old
May 2018 - Apr 2019
Contributions:7 commits, 10 pushes in 11 months
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