Principal Software Engineer at Walmart Global Tech India
Bengaluru, Karnataka, India
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Summary
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Senior
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Top School
Nilabh Sagar is a Principal Software Engineer and enterprise architect based in Bengaluru with two decades of experience designing and delivering large-scale, cost-efficient cloud-native platforms. He currently leads the Feature Store and AI Catalog platform at Walmart Global Tech, having authored the white paper and driven its production rollout across 2,500+ features while blending open-source and managed cloud services. Previously he shaped OCI-native AI/ML lifecycle infrastructure at Oracle and modernized high-throughput, event-driven membership and subscription systems at Walmart using Azure, achieving significant performance and cost gains. Known for pragmatic architectural decisions, he has a track record of reducing operational costs (e.g., 60% Cosmos DB savings) and improving throughput by orders of magnitude. He also contributes to open-source—fixing metric and threading issues in the widely used Datadog Python client—showing hands-on backend craftsmanship alongside strategic leadership. An IIM Bangalore executive alumnus with deep engineering roots, he pairs system-level vision with practical implementations that move ML and analytics platforms into production.
10 years of coding experience
15 years of employment as a software developer
MCA Computer Applications, MCA Computer Applications at B. M. S. College of Engineering
Bachelor of Computer Applications Computer Science, Bachelor of Computer Applications Computer Science at Makhanlal Chaturvedi National University of Journalism and Communication, Bhopal
Executive Education Program Business Administration and Management General, Executive Education Program Business Administration and Management General at Indian Institute of Management Bangalore
Contributions:9 commits, 1 PR, 7 comments in 2 months
Contributions summary:Nilabh primarily contributed to the `datadogpy` library by fixing bugs related to metric types and ensuring correct data formatting. They addressed issues with thread statistics, guaranteeing the accurate emission of metric types like gauge and rate. Additionally, the user made changes to incorporate the proper intervals in the metric reporting, which also involved merging code from the upstream master branch.
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