About
I'm a senior backend engineer specializing in designing and scaling high-throughput distributed systems. Whether it's decoupling legacy monoliths into robust microservice architectures or constructing fault-tolerant data pipelines processing hundreds of gigabytes per hour, my focus lies entirely on backend resilience and engineering velocity.
When I'm not untangling profound database bottlenecks, optimizing OpenSearch queries, or orchestrating containers smoothly, I continuously strive to master the intricacies of modern architectural patterns.
Core Arsenal
Experience
Senior Backend Engineer @ Deloitte (Disruption Office)
Case Study: 0-to-1 Microservices Platform
Legacy SAP/Salesforce systems were throttling operations. I architected and shipped a complete Node.js microservices platform on AWS in just 3 months. By decentralizing domain logic and implementing robust API gateways, we generated an estimated $400k in annual cost savings and drastically reduced operational latency.
Case Study: Distributed ETL at 300+ GB/hr
Data fragmentation across heterogeneous databases (SQL, NoSQL), external APIs, and flat files was leading to severe data loss. I designed distributed Python ETL pipelines processing 300+ GB/hr. Implementing automated reconciliation protocols across 3M+ records entirely eliminated data loss and provided teams with real-time, synchronized reporting.
Case Study: Solving the N+1 Bottleneck
An enterprise Licensing Module (React, Node.js, Express) serving 10+ brands was suffering from critical performance degradation due to N+1 querying. I executed a complex refactor involving strategic MySQL indexing and query optimization, paired with a zero-downtime OpenSearch cluster re-indexing, resulting in lightning-fast search capabilities and significantly stabilized backend execution.
Featured Projects
Currently designing an end-to-end distributed event processing architecture capable of ingesting and transforming millions of real-time events. This project demonstrates deep technical depth in handling concurrency, fault tolerance, and message queuing at massive scale.
- Horizontal scaling via Docker/Kubernetes
- Zero-data loss dead-letter queues
- Low-latency consensus and processing
Let's build
something great.
I read every single message. Whether you're recruiting for a high-velocity startup, looking for a technical co-founder, or just want to chat about system architecture—drop a line.