Umer Farooqi

Led technical strategy for 70+ engineers across multiple product teams by driving architecture decisions, establishing engineering standards, and reducing deployment incidents by 70% through structured code reviews, peer reviews, and operational runbooks. Architected and scaled an event-driven, cloud-native microservices platform processing 50M+ monthly API requests by defining service boundaries and RESTful API contracts, reducing integration issues by 40% and accelerating deployment cycles by 60%. Implemented and optimized CI/CD pipelines and DevOps practices, improving platform reliability and increasing availability from 98.5% to 99.95% uptime. Mentored engineers through architecture reviews, code reviews, and best practices, improving code quality metrics by 45%.

Architected and delivered a headless commerce platform serving 200K+ concurrent users and generating $5M+ annual GMV, processing 15M+ daily API requests while maintaining <200ms p99 latency. Designed and optimized scalable RESTful APIs using NestJS, Laravel, and Node.js, improving database performance by 62% via indexing, query optimization, and caching, and reducing infrastructure costs by $50K annually. Designed and implemented automated CI/CD pipelines and DevOps workflows, reducing deployment time from 45 minutes to 10 minutes and enabling 10+ production deployments per day with 99.5% deployment reliability. Led cross-functional teams, improving API development best practices and reducing client integration time by 35%.

Engineered and scaled distributed backend systems supporting 100K+ daily active users and processing 50M+ monthly transactions while maintaining 99.9% availability and average response time of 300ms. Led migration from a monolithic architecture to a microservices-based architecture (12+ services), enabling independent deployments, accelerating release cycles by 3x, and supporting 10x user growth. Optimized database performance across 8 microservices using query optimization, strategic indexing, and caching, improving query performance by 60% and reducing database load by 50%.