Senior Java Developer Microservices, Cloud, Spring Boot

GOPI MAREEDU

+1-919-***-**** — **********@*****.*** — www.linkedin.com/in/mareedugopi

PROFESSIONAL SUMMARY

Full Stack Java Developer with 4.5+ years of experience building high-performance, scalable microservices and distributed systems. Expert in Java, Spring Boot, Kafka, AWS, React, and Kubernetes. Proven track record of reducing latency by 40%, improving system throughput, and delivering mission-critical features for financial services and e-commerce platforms serving millions of users. TECHNICAL SKILLS

Languages: Java 17/11/8, Python, JavaScript (ES6+), TypeScript, SQL Backend: Spring Boot, Spring Cloud, Spring Security, Microservices, REST APIs, GraphQL, JPA/Hibernate, Spring Batch, OAuth2, JWT

Frontend: React, Redux, Angular, RxJS, TypeScript, HTML5, CSS3, Axios Data: PostgreSQL, MySQL, MongoDB, DynamoDB, Redis, AWS S3, ElasticSearch Messaging: Kafka, AWS SQS, AWS SNS, RabbitMQ

Cloud & DevOps: AWS (EKS, Lambda, S3, EC2, RDS), Docker, Kubernetes, Terraform, Jenkins, Git, Maven, CI/CD

Monitoring: Prometheus, Grafana, Splunk, New Relic, Spring Boot Actuator, ELK Stack Testing: JUnit 5, Mockito, Selenium, JMeter, Integration Testing, TDD PROFESSIONAL EXPERIENCE

Full Stack Java Developer June 2024 – Present

Wells Fargo, TX

• Architected and deployed 8+ microservices using Java 17, Spring Boot, and PostgreSQL, reducing loan pro- cessing time by 40% through optimized JPA queries and database indexing strategies

• Built secure authentication systemwithSpringSecurity,JWT, and OAuth2 supporting role-based access control for 50K+ users across customer, employee, and manager tiers

• Engineered real-time search engine using ElasticSearch with fuzzy search, geo-queries, and aggregations, enabling sub-100ms query response times for 2M+ loan records

• Designed event-driven notification system using AWS SNS and Kafka, processing 100K+ messages daily with 99.9% delivery success rate

• Implemented automated risk scoring engine using Spring Boot and ElasticSearch aggregations, analyzing credit, income, and employment data to generate risk scores with 95% accuracy

• Deployed containerized services on AWS EKS with Kubernetes HPA, achieving zero-downtime deployments and 40% cost reduction through auto-scaling

• Established CI/CD pipelines with Jenkins, Git, and SonarQube, reducing deployment time from 2 hours to 15 minutes while maintaining 90%+ code coverage

• Built Angular dashboards with RxJS for real-time loan status updates, integrated with Spring Boot REST APIs serving 10K+ concurrent users

• Configured Prometheus and Grafana monitoring stack tracking 50+ metrics including API latency (p95 200ms), JVM memory, and error rates

Java Developer October 2023 – June 2024

Optum, NJ

• Developed distributed order processing system using Java 11, Spring Boot, Kafka, and MongoDB, handling 500K+ daily transactions with 38% reduction in fulfillment delays

• Built high-performance REST APIs with Redis caching and MySQL, achieving sub-10ms response times for inventory lookups across 500+ retail locations

• Created React/Redux dashboards with real-time order tracking and analytics, integrating Prometheus metrics and Grafana visualizations for operational insights

• Implemented product search engine with ElasticSearch supporting autocomplete, fuzzy matching, and geo- filtering for 1M+ SKUs with 99.5% accuracy

• Automated inventory synchronization using AWS Lambda, Spring Batch, and MongoDB, reducing data incon- sistencies by 85%

• Engineered secure authentication with Spring Security and JWT, implementing RBAC for employee, manager, and admin roles

• Optimized order routing algorithm using Java concurrency and ElasticSearch geo-queries, reducing average delivery time by 25%

• Integrated Spring Boot Actuator with Splunk and New Relic for distributed tracing, reducing MTTR from 45 to 12 minutes

Software Engineer May 2020 – July 2022

PwC, India

• Built payment authorization and settlement microservices using Java 11, Spring Boot, and DynamoDB, pro- cessing 200K+ daily transactions with 99.95% uptime

• Developed event-driven architecture with Kafka for real-time payment processing, reducing transaction latency by 60%

• Implemented retry mechanisms with AWS SQS and Java concurrency, decreasing payment failure rate from 3% to 0.5%

• Created React merchant dashboards with Redux Toolkit and Axios for payment tracking, refund management, and analytics

• Deployed PCI-DSS compliant services on AWS EKS with encrypted S3 storage for receipts and transaction records

• Established monitoring infrastructure with Prometheus, Grafana, and New Relic, tracking payment success rates and API performance

EDUCATION

Master of Science in Data Science — Wichita State University, Kansas Bachelor of Computer Science — Veltech University, India KEY ACHIEVEMENTS

• Reduced loan processing latency by 40% through microservices optimization and ElasticSearch implementation at Wells Fargo

• Decreased order fulfillment delays by 38% by engineering high-throughput Kafka-based event processing system at Optum

• Achieved 99.95% uptime for payment systems handling 200K+ daily transactions with zero data loss at PwC

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