Vedant Ranjan

Software Engineer

Gurugram, Haryana, India4 yrs 10 mos experience

Key Highlights

Architected a scalable analytics platform for real-time KPI tracking.
Reduced production incidents by 80% through optimization.
Expert in designing distributed microservices on AWS.

Stackforce AI infers this person is a Backend Engineer specializing in scalable systems and microservices architecture.

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Skills

Core Skills

JavaSystem Design

Other Skills

Core JavaData StructuresFastAPISQLAmazon Web Services (AWS)TerraformReactive ProgrammingPython (Programming Language)REST APIsMockitoJUnitMicroservicesHTMLCommunicationProgramming

About

Software Engineer with 5+ years of experience building scalable backend systems using Java and Spring Boot. Currently at Nielsen as MTS-2, working on scaling and building new systems. My core strengths are in: 1.Designing distributed microservices on AWS 2.Writing high-performance, production-grade Java 3.System design for scale , from schema to deployment Outside of work, I actively practice DSA and enjoy thinking through system design problems. Open to conversations about backend engineering, platform engineering, and distributed systems roles.

Experience

4 yrs 10 mos

Total Experience

2 yrs 11 mos

Average Tenure

1 yr 11 mos

Current Experience

Nielsen

2 roles

Member of Technical Staff-2

Promoted

Mar 2026 – Present · 3 mos

◦ Architected and built a scalable analytics platform (similar to Matomo) , processing ˜10K+ events/day and
enabling real-time KPI tracking across multiple teams, reducing manual reporting effort by more than 80%.
◦ Reduced production incidents by 80% through continuous code refactoring, optimization, and
implementation of best practices, significantly improving system stability.
◦ Owned end-to-end delivery for the Italian business vertical from Covercare integration(Third Party)
to ServiceNow ticket management, ensuring smooth business operations.
◦ Designed and optimized high-performance APIs using FastAPI, improving response times by 30% and
enabling better scalability across services.
◦ Optimized complex SQL queries by identifying proper indexes and memory allocation, reducing execution
time from 1h 20m to 18m (77% improvement in performance)
◦ Created and published a reusable common package containing shared code used across multiple
microservices and cross-team projects, reducing code duplication and improving development efficiency.