Headline

Java Backend Engineer @ Nielsen | Distributed Systems & Event-Driven Pipelines | AWS (S3, SQS, EC2) | Spring Boot

About

Java Backend Engineer with 2+ years of production experience building distributed systems, event-driven pipelines, and cloud data infrastructure on AWS. At Nielsen, I own end-to-end delivery of audience data-crediting systems processing millions of records per cycle across 31+ global markets, coordinating releases with product, QA, and operations teams across 5+ time zones. Selected results: • 25x audio-fingerprint search acceleration — designed an LSH-based indexing layer cutting brute-force comparisons from ~50,000 to ~200 candidates at >99.9% accuracy • Production incident root-caused to a missing SQL index: query latency 45s → under 2s, 30% recurring failure rate eliminated • Dynamic EC2 capacity management with automatic Spot-to-On-Demand failover for uninterrupted, cost-optimised media processing • At e6data: 3x analytical throughput via an Apache Arrow C++ Parquet reader bridged to Java through JNI Core stack: Java · C++ · Spring Boot · REST microservices · AWS (S3, SQS, EC2) · SQL Server / PostgreSQL / MySQL · GitLab CI/CD Open to backend roles that are remote-first, Europe-based (relocation + sponsorship), or India-based at the next level. Best reached at ashishvarma1729@gmail.com.

Location

Bengaluru

AI stack

claude code

gemini

github copilot

kiro

langchain

langgraph

Work experience

Software Engineer at Nielsen, Jul 2024 - Present · 2 yrs 5 mos, Bengaluru, – End-to-end ownership: Owned delivery of Java-based audience data crediting systems, processing millions of records per cycle for the France market across 31+ country audience measurement platforms globally. – Audio fingerprint search optimisation: Designed an LSH-based indexing layer for a Hamming-distance audio fingerprinting engine, cutting brute-force comparisons from ~50,000 to ~200 at >99.9% match accuracy — a 25× throughput improvement. – Compute cost optimisation: Implemented dynamic EC2 instance management with On-Demand base capacity and automatic Spot-to-On-Demand failover for uninterrupted, cost-optimised media processing. – Production incident resolution: Root-caused recurring pipeline failures in a Java-to-C++ workflow to a missing composite SQL index: query latency 45s → under 2s, 30% recurring failure rate eliminated. – Event-driven architecture: Designed AWS SQS-based async job coordination across dependent Java services, decoupling pipeline stages for better throughput in multi-stage batch workflows. – Distributed batch pipelines: Engineered multi-stage Java batch pipelines processing large vendor datasets through validation, transformation, and reconciliation with high reliability. – Java microservices: Built and maintained Java REST microservices integrated with a downstream C++ crediting engine; coordinated SLA-aligned releases with product, QA, and operations teams across 5+ time zones. – CI/CD & observability: Added structured JSON logging and schema validation guardrails in GitLab CI/CD pipelines to detect malformed vendor inputs early and reduce silent failures. – Cross-functional delivery: Partnered with Mediametrie (France) across 3 continents for joint market delivery, ensuring SLA compliance on every release cycle. Stack: Java, C++, Spring Boot, REST APIs, AWS S3, AWS SQS, AWS EC2, SQL Server, GitLab CI/CD

Performance and Research Intern at e6data, Jul 2023 - Dec 2023 · 6 mos, Bengaluru, Karnataka, India

Summer Intern at Swecha Telangana, May 2022 - Jul 2022 · 3 mos, Hyderabad, Telangana, India

Education

Minor in finance, Finance, General, Birla Institute of Technology and Science, Pilani - Goa Campus

Bachelor of Engineering - BE, Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani - Goa Campus

Public links

github: https://github.com/AshishVarma7

leetcode: https://leetcode.com/ashishvarma1729