Mayank Jha

Designed and built a comprehensive microservices-based ERP platform using Go, delivering enterprise solutions to 2000+ businesses including Fortune 500 companies across 15+ countries.

Accelerated system performance by 40% through development of 12+ high-performance microservices leveraging Go goroutines for concurrent processing and optimal resource utilization.

Established robust inter-service communication by deploying Apache Kafka and Zookeeper messaging architecture, successfully handling 1M+ daily events with zero data loss.

Automated bulk data processing capabilities that eliminated 85% of manual intervention while seamlessly ingesting 15000+ employee records through streamlined pipeline architecture.

Architected comprehensive Java and Spring Boot security framework for enterprise ERP system serving 2000+ businesses, fortifying 15+ microservices and safeguarding 500,000+ user records with zero security breaches over 18 months through role-based access control and JWT authentication protocols.

Engineered centralized Java authentication library with OAuth 2.0 integration deployed across 12+ microservices, slashing security vulnerabilities by 95% (47 to 2 critical issues), accelerating authentication response time by 60%, and streamlining new service development by 40%.

Enhanced system efficiency by 30% through implementation of caching strategies using Redis for role-based access control, optimizing performance for 1M+ daily authorization requests.

Maintained 99.9% uptime by orchestrating Kubernetes-based deployments with intelligent auto-scaling, ensuring uninterrupted service delivery for global enterprise customers.

Engineered and delivered a mission-critical hotfix deployment for the timestamp tracking system within a 48-hour emergency window, resolving severe performance degradation issues threatening business continuity for enterprise clients.

Diagnosed and eliminated critical performance degradation affecting 1M+ daily requests by executing root cause analysis using JProfiler and VisualVM, optimizing thread pool configurations and eradicating memory leaks, delivering 45% reduction in heap usage, 55% improvement in thread utilization, and sustaining 98.7% uptime for 12+ months.

Automated data consolidation for global MRA datasets using Python, eliminating 90% of manual intervention and processing 10000+ records daily.

Utilized openpyxl and pandas libraries for data-cleaning processes, enhancing data integrity for marketing analytics by 30% across 5+ business units.