I design and build reliable distributed systems, backend platforms, and high-throughput microservices. 3+ years of engineering experience across enterprise and financial environments.
Implementation of a distributed key-value store using the Raft consensus algorithm. Supports leader election, log replication, and fault-tolerant state machine replication across nodes.
Simplified MapReduce framework for distributed data processing. Supports task scheduling, worker coordination, and fault recovery with task retry on failure.
Microservice-based document extraction pipeline that processes OCR documents across upload, extraction, validation, and callback routing services.
How MapReduce distributes large-scale data processing across a cluster — covering the programming model, task scheduling, fault recovery, and what I learned building a simplified framework in Go.
7 min read
How Kafka achieves high throughput, fault tolerance, and exactly-once semantics — covering partitions, replication, consumer groups, and the log-based storage model.
6 min read
A deep dive into how Raft achieves distributed consensus through leader election, log replication, and safety guarantees — with implementation notes from building a Raft-based key-value store in Go.
5 min read