Sushma Lingam

About Sushma Lingam

Seasoned Full Stack Java Developer with 5+ years of experience in developing robust, scalable applications for financial services and e-commerce sector.• Expertise in microservices architecture, having designed and implemented high-throughput systems processing millions of transactions daily. Experienced in cloud technologies, like AWS services including IAM, EC2, Lambda, RDS, and S3.• Proficient in Java 8+, Spring Boot, Spring MVC, and RESTful API development, with a strong focus on performance optimization and security.• Skilled in database management and optimization, working with MySQL, MongoDB, PostgreSQL, and implementing ORM frameworks. Well-versed in front-end technologies including Angular, React.js, and responsive design principles.• Strong background in DevOps practices, utilizing Docker, Kubernetes, Jenkins, and implementing CI/CD pipelines for streamlined deployments.• Adept at Agile methodologies, with a track record of successful project delivery and stakeholder management across multiple time zones.• Proven ability to improve system performance, having achieved significant reductions in latency, query times, and deployment cycles.• Committed to code quality and best practices, regularly conducting code reviews, and maintaining high test coverage using JUnit and Mockito.

Experience

1. Full-stack Developer

   JPMorganChase

   May 2023 — Present · US

   Spearheaded the development of a high-throughput payment processing microservices architecture using Java 11 and Spring Boot 2.5, processing over 1.5 million transactions daily with 99.99% uptime.• Designed and implemented 7 event-driven microservices using Apache Kafka for message queuing, reducing system latency by 45% and improving scalability.• Developed RESTful APIs using Spring Web MVC, implementing OAuth 2.0 with JSON Web Tokens (JWT) for secure authentication, resulting in a 30% reduction in unauthorized access attempts.• Utilized Spring Data JPA for database operations, optimizing queries and implementing database indexing strategies that improved read performance by 40%.• Implemented circuit breaker patterns using Resilience4j to enhance system fault tolerance, reducing cascading failures by 60% during peak load times.• Refactored critical algorithms using Java 8 Streams API, improving data processing speed by 35% for large datasets.• Containerized applications using Docker and orchestrated deployments with Kubernetes, achieving a 50% reduction in deployment time and improving resource utilization by 35%.• Integrated Elasticsearch for full-text search capabilities, enhancing transaction lookup speed by 70% for customer service operations.• Contributed bug fixes and performance improvements to 3 open-source libraries used in the project, benefiting the wider developer community.• Implemented comprehensive unit testing using JUnit 5 and Mockito, achieving 95% code coverage and reducing post-release defects by 55%.• Utilized AWS services including S3 for object storage, RDS for PostgreSQL databases, and CloudWatch for centralized logging and monitoring, improving system observability by 50%.• Implemented continuous integration and deployment (CI/CD) pipelines using Jenkins, automating build, test, and deployment processes, which reduced release cycles from bi-weekly to daily.

Education

• MLR Institute of Technology

  Bachelor's degree

  2015 — 2019

• University of Dayton

  Master's degree

  2022 — 2024