Nithish Kumar G

Backend Engineer

Bangalore Urban, Karnataka, India3 yrs 8 mos experience

Key Highlights

Expert in high-performance microservices and distributed systems.
Reduced client onboarding time from 60 days to just 7 days.
Improved MapReduce recovery time by 60% through optimization.

Stackforce AI infers this person is a Backend Engineer specializing in SaaS and real-time data streaming solutions.

Contact

Skills

Core Skills

MicroservicesReal-time Data StreamingJavaPerformance EngineeringDistributed SystemsAngular

Other Skills

ZMQHazelcastCachingConcurrencyOOPSOLIDJStackGC tuningThread dump analysisPostgreSQLMultithreadingSpring BootMySQLLinuxEvent-driven

About

I’m a Backend Engineer (3.9+ years) specializing in high-performance microservices, distributed systems, real-time data streaming, and JVM optimization.I build systems that are fast, fault-tolerant, and scalable, and I love solving backend problems related to concurrency, caching, throughput, latency, and system design. 𝗪𝗵𝗮𝘁 𝗜 𝘄𝗼𝗿𝗸 𝗼𝗻 - • Java, Spring Boot, Microservices • Distributed Systems (ZMQ, Hazelcast, Pub/Sub) • Caching, Load Balancing, Asynchronous Messaging • JVM Internals, GC Tuning, Thread Dump Analysis • Real-time data streaming and high-volume pipelines • PostgreSQL, HBase, MapReduce,Hadoop 𝗡𝗼𝘁𝗮𝗯𝗹𝗲 𝗪𝗼𝗿𝗸 - • Built a real-time streaming service using ZMQ + Hazelcast • Automated deployment workflows (reduced onboarding 60 days → 7 days) • Improved MapReduce recovery time by 60% • Designed concurrency, caching and messaging flows for high throughput• Performed deep JVM-level debugging and performance tuning

Experience

3 yrs 8 mos

Total Experience

Average Tenure

Current Experience

Pelatro

3 roles

Senior Development Engineer

Apr 2026 – Present · 2 mos · Bengaluru · On-site

Software Developer

Promoted

Aug 2023 – Mar 2026 · 2 yrs 7 mos · Bengaluru · On-site

𝗘𝘃𝗲𝗻𝘁𝗙𝗹𝗼𝘄 𝗦𝘁𝗿𝗲𝗮𝗺𝗲𝗿 – 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 𝗦𝗲𝗿𝘃𝗶𝗰𝗲
Designed & developed a real-time streaming microservice using ZMQ pub-sub patterns for low-latency event distribution.
Implemented timestamp & customer-range based subscription logic, improving downstream processing efficiency.
Integrated Hazelcast distributed caching,If a node crashed or restarted, another node could reconstruct and continue execution from the persisted runtime state.
Added fault-tolerant recovery and concurrency-safe workflows for seamless restarts during failures.
𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺
Built an internal automation system reducing client onboarding time from 45–60 days → 7–10 days.
Designed scalable workflows using SOLID, OOP, and reusable system components.
𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 & 𝗝𝗩𝗠 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻
Optimized system performance for pipelines processing millions of daily events.
Performed JStack, JMap, GC tuning, thread dump analysis, and memory profiling to remove bottlenecks.
Improved MapReduce recovery pipeline performance by 60%.
Developed efficient data archiving utilities to reduce storage pressure and improve stability.

JavaZMQHazelcastMicroservicesReal-time data streamingCaching+1

Engineer Trainee - Development

Aug 2022 – Jul 2023 · 11 mos · Bengaluru · On-site

Contributed to backend modules across microservices, data pipelines & streaming flows.
Strengthened fundamentals in Java, PostgreSQL, multithreading, and distributed system components.

JavaPostgreSQLMultithreadingDistributed systemsDistributed Systems