Aman Jaiswal

Led the development and optimization of high-performance microservices, data pipelines, and cloud-native solutions, significantly enhancing system efficiency and reliability for high-traffic applications.

• Optimized high-traffic MongoDB collections through strategic indexing and aggregation pipeline refactoring, reducing average query response time by 25% and lowering database CPU utilization by 30%.
• Implemented KEDA (Kubernetes Event-driven Autoscaling) for event-processing microservices, achieving efficient resource utilization by scaling to zero during idle periods and instantly handling high-volume message bursts.
• Architected a high-throughput BigQuery pipeline that dynamically joins and paginates massive datasets, delivering complex query results in sub-second timeframes to enhance interactive reporting capabilities.
• Boosted application throughput by 300% by re-architecting a core data processing module from a single-threaded to a multi-threaded design, eliminating performance degradation.
• Implemented comprehensive monitoring and alerting for GCP-hosted services using OpenTelemetry, structured logging, and metrics dashboards, improving proactive issue detection by 60% and enhancing overall system reliability.

Collaborated with senior developers to optimize Spring Boot applications and enhance software reliability through comprehensive testing practices.

• Collaborated with senior Java developers to optimize Spring Boot applications, contributing to scalable REST APIs deployed in production environments.
• Enhanced application reliability by implementing 100+ unit tests using JUnit and Mockito, boosting code coverage by 30% and reducing production defects by 20%.

Developed a secure, full-stack file management system with a robust Django REST API backend and a modern React frontend.

Awarded for demonstrating exceptional problem-solving and technical skills in a competitive college-level hackathon, showcasing innovative software development capabilities.