Rahul Chaudhry is a data engineering lead with 11 years of experience building scalable ETL pipelines, data warehouses, and analytics platforms across federal and private sectors, currently driving data science initiatives at Peraton and FDIC. He combines deep SQL and Python expertise with cloud-first tooling (AWS, Azure, GCP) to manage datasets exceeding 3 TB and deliver production-ready data models and reporting. Rahul’s background spans hands-on integration work—Talend, Informatica, AWS Glue—and monitoring stacks like Splunk and Datadog, enabling fast incident resolution and data quality. Notably, he contributes to the Go language repo on build and platform compatibility issues, reflecting a pragmatic open-source streak and systems-level curiosity beyond typical data roles. Certified across AWS, Azure, GCP, and SAFe Agile, he excels at translating complex requirements into reliable, auditable pipelines that empower cross-functional decision-making.
11 years of coding experience
4 years of employment as a software developer
Master's degree Management Information Systems, General, Master's degree Management Information Systems, General at University at Buffalo School of Management, The State University of New York
Bachelor in Technology Computer Science, Bachelor in Technology Computer Science at University School of Information, Communication & Technology, Guru Gobind Singh Indraprastha University, New Delhi
Master of Science Management Information Systems, General, Master of Science Management Information Systems, General at University at Buffalo, State University of New York
Bachelor of Technology Computer Engineering, Bachelor of Technology Computer Engineering at Guru Gobind Singh Indraprastha University
Contributions:1 commit, 3 comments, 4 issues in 1 day
Contributions summary:Rahul primarily contributed to the Go programming language repository by fixing build issues, optimizing the build process, and addressing platform-specific compatibility issues. They focused on build configurations, particularly related to Android/ARM64, including setting build defaults and enabling specific features. Their contributions also involved correcting quoting in build scripts and making necessary adjustments for iOS detection.
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