Open to opportunities Backend Engineer

Bhavesh
Lohana

Software Engineer @ Barclays  ·  Pune, India

Backend engineer focused on building reliable, high-scale systems. 3+ years of experience designing services that handle millions of records daily, working across distributed architectures, and optimizing performance where it matters. Always looking for problems worth solving.

// work history

Experience

Backend engineer specialising in distributed systems, data pipelines, and high-throughput Java services.

Barclays Aug 2022 — Present
Software Engineer · Pune, India
  • Designed Reference Data Derived Rule Engine — a Spring Boot framework dynamically deriving data via configurable condition-action rules across 100M+ records.
  • Led end-to-end migration of Bucketing Service from .NET + MongoDB to Spring Boot + Oracle, achieving a 2x performance boost through backend re-architecture and SQL optimization.
  • Built Grading Service using Scala + Apache Spark, processing and grading 12M+ issuers daily in under 9 minutes via partition tuning, broadcast joins, and executor optimization.
  • Enhanced Orchestrator — a 7+ microservice event-driven platform connecting Data Mart, ETL, and OLAP systems — reducing inter-service latency by 30%.

// what i've built

Projects

01 Production Ready

Distributed Rate Limiter

Production-grade rate limiting service and reusable Spring Boot Starter library. Supports three algorithms with atomic Redis Lua scripts, dynamic per-client configuration, and plug-and-play @RateLimit annotation via AOP.

  • 3 algorithms — Fixed Window, Sliding Window Log, Token Bucket with atomic Lua
  • 86 req/sec — k6 load tested, all responses under 200ms
  • Published Spring Boot Starter to GitHub Packages — zero-config integration
  • Full CI/CD pipeline with GitHub Actions, Docker Hub, Render deployment
  • Real-time observability via Prometheus + Grafana
Java Spring Boot Redis Lua Docker Prometheus Grafana
02 Production Ready

CacheForge

Cache simulation and benchmarking service supporting 8 eviction algorithms and 6 configurable workload generators. Real-time WebSocket progress streaming, concurrent simulation mode, and nanosecond-precision latency telemetry.

  • 8 algorithms — LRU, LFU, FIFO, MRU, ARC, CLOCK, Random, TTL enabled
  • 6 workloads — Zipfian, Hotspot, Temporal, Sequential, Random, TTL
  • WebSocket/STOMP real-time progress streaming during simulations
  • LatencyTrackingCache decorator — nanosecond precision without AOP overhead
  • Micrometer → Prometheus → Grafana metrics pipeline
Java Spring Boot WebSocket Prometheus Grafana Docker

// tech stack

Skills

Languages

Java Scala Python SQL C/C++ Lua

Frameworks & Technologies

Spring Boot Apache Spark Redis Flask Node.js

Tools & Platforms

Docker GitHub Actions Prometheus Grafana Oracle MySQL Git IntelliJ IDEA
Expert Proficient Familiar

Let's connect

Open to senior backend and SDE-2 roles. If you're building something interesting with distributed systems, data pipelines, or Java services — let's talk.