• Engineered scalable backend services processing 500+ daily transactions using Java, Spring Boot, and Python within a cloudnative architecture.

• Designed and deployed high-performance RESTful APIs, increasing data processing efficiency by 15% and enabling seamless system integration.

• Re-architected monolithic components into micro services, improving scalability, fault tolerance, and independent deployments.

• Optimized AWS infrastructure (EC2, Lambda, Dynamo DB), reducing response latency by 10–15% under peak load.

• Automated CI/CD pipelines using Docker and Git Hub Actions, accelerating release cycles by 20%.

• Diagnosed and resolved critical production issues, reducing MTTR by 25% and improving service reliability.

• Enhanced observe ability using Cloud Watch logging, monitoring, and alerting, enabling proactive issue detection.

• Implemented caching strategies and performance tuning techniques to support low-latency, high-throughput systems.

• Boosted system throughput by 30% through advanced database indexing and connection pooling optimization.

• Maintained 99.9% uptime across distributed financial systems handling high-volume transactions.

• Reduced query latency by 30%, improving backend performance and user experience.

• Automated operational workflows using Python, reducing manual effort by 40%.

• Mitigated security vulnerabilities through secure coding practices and code reviews.

• Eliminated recurring production issues by 60% using root cause analysis (RCA) and debugging strategies.

• Designed scalable backend modules aligned with event-driven and distributed system architecture principles.

• Re factored legacy systems to improve maintainability, performance, and scalability.