Nikita Pande is a Staff Data Engineer based in Bengaluru with a strong 14-year engineering background and eight years of focused experience building cloud-native data platforms at enterprises like Visa, JPMorgan Chase, and American Express. He blends deep GoLang expertise, platform engineering (GKE, Terraform, hybrid cloud), and service-mesh experience into reliable, production-grade systems and operational tooling. Nikita contributes to notable CNCF projects—such as Volcano and Kuma—where he’s fixed core scheduler logic, hardened dataplane validation, and addressed security and testing gaps, showing hands-on familiarity with distributed scheduling and observability. He began his career in avionics and radar systems at Hindustan Aeronautics, which adds a systems-level rigor and testing discipline uncommon in purely cloud-native engineers. A high-achieving NIT Raipur alumnus with a 9.33/10 GPA, he is actively learning Big Data technologies and AI, demonstrating a continuous-learning mindset that complements his platform leadership.
8 years of coding experience
9 years of employment as a software developer
Kendriya Vidyalaya N.T.P.C.
Bachelor of Technology (B.Tech.), Electronics and Telecommunication, 9.33/10 (Honors), Bachelor of Technology (B.Tech.), Electronics and Telecommunication, 9.33/10 (Honors) at NIT Raipur
🐻 The multi-zone service mesh for containers, Kubernetes and VMs. Built with Envoy. CNCF Sandbox Project.
Role in this project:
Backend Developer
Contributions:10 reviews, 8 commits, 10 PRs in 1 year
Contributions summary:Nikita primarily contributed to the backend of the Kuma service mesh. They addressed a nil-pointer issue in the dataplane validation and added configuration options for Postgres, including max idle connections. Furthermore, they implemented log rotation functionality across several Kuma applications. Additionally, the user fixed a security vulnerability by updating a Go JWT library.
Contributions:7 commits, 5 PRs, 2 comments in 1 month
Contributions summary:Nikita primarily focused on code improvements and bug fixes within the project's core components, specifically the scheduler framework. Their work involved modifications to the session management logic, suggesting an understanding of resource allocation and job execution flow. Additionally, the user contributed to linting and testing-related tasks, including fixes in the e2e and admission packages, which implies familiarity with the project's testing infrastructure and overall code quality.
golangbigdatabatchmachine-learningkubernetes
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Nikita Pande - Staff Data Engineer (Data Platform)