Naman Kanwar is a data engineer with 9 years of cross-industry experience building performant ETL pipelines, search and matching systems, and analytics platforms for companies including FanDuel and Walmart Global Tech. He combines a strong software engineering background—C++, Python, Spark, SQL—and machine learning training from a master’s program to deliver production-grade data solutions that cut latency and storage costs. Notable projects include a phonetic/fuzzy matching search that sped lookups to under 2 seconds for tens of millions of records, an automated testing and CRON-based workflow that saved 120 work hours, and a CAPTCHA-breaking scraper with 90% accuracy for cybersecurity research. Comfortable across backend, API, and data visualization stacks, he has a track record of turning research prototypes into deployed systems used by hundreds of users. Based in Atlanta, he brings both academic rigor and pragmatic engineering to fast-moving product teams.
9 years of coding experience
7 years of employment as a software developer
Master's degree Computer Science (Machine Learning), Master's degree Computer Science (Machine Learning) at Georgia State University
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