Engineering resilient core systems for modern fintech.
Building high-performance, distributed systems that handle millions of requests at OneCard. Specialized in low-latency infrastructure and financial ledger integrity. Based in Pune, India.
Reduced P99 latency across core payment gateways through JVM tuning and caching strategies.
Managing transactions with strict ACID compliance and zero-loss reconciliation pipelines.
System designed to scale up to 50k+ QPS during peak holiday traffic cycles.
Professional
Execution
Selected Works (2021-Present)
OneCard (Fintech)
SDE 2 | PUNE-
terminal
Led migration to Go-based microservices, achieving a 3x improvement in throughput and 60% reduction in memory footprint compared to legacy systems.
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database
Architected a real-time fraud detection bridge processing 5k+ events per second using Kafka and Flink with sub-50ms processing time.
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security
Redesigned the RBAC system to handle granular permissions for 100+ internal services, ensuring zero downtime during the migration phase.
Engineering Artifacts
Distributed Rate Limiter
A sliding-window rate limiter designed for high-availability clusters. Solves the 'thundering herd' problem using Redis Lua scripts for atomic operations.
Used Token Bucket for smooth traffic shaping over Leaky Bucket to avoid request bursts during high-load intervals.
Payment Reconciliation Engine
Automated the matching of 1M+ bank settlement records daily. Handles multi-currency scenarios and partial payment exceptions with a 99.9% match rate.
Idempotent consumers ensure no double-processing of settlement files. Implemented using Saga pattern for distributed consistency.
Designing a Low-Latency Ledger Service
How to maintain double-entry bookkeeping consistency for 50k transactions per second while maintaining a sub-20ms response time for balance queries.
Separated Read and Write paths. Used PostgreSQL for the source of truth (Append-only Ledger) and Redis for materialized balance views.
By moving from direct relational lookups to pre-computed materialized views in Redis, we achieved a 95% reduction in query latency during peak periods.
Languages
Infrastructure
Databases
Engineering Mindset
I believe in the First Principles approach to problem-solving. My work isn't just about shipping code; it's about evaluating architectural trade-offs, ensuring future scalability, and taking complete ownership of the system's lifecycle.
Clean Code Advocate
Focusing on maintainability and readability as much as performance.
Trade-off Analysis
Understanding when to choose consistency over availability (CAP theorem).