VAISHNAVI SHARMA
Lucknow.About
Backend Engineer skilled in cloud-native microservices, distributed systems, and data-intensive applications using Spring Boot, Apache Spark, Kubernetes, Kafka, and AWS. I have optimized large-scale storage systems, enhanced system resilience by 99 percent using fault-tolerant designs, improved request latency by up to 60 percent, and successfully containerized enterprise applications to ensure scalable and high-performing deployments.
Work
Gupshup
|SWE-1
Summary
Generic Storage Service | Developed a highly optimized storage service leveraging Spring Boot and Apache Spark for large-scale data processing, with Kafka for inter-service message streaming, AWS S3 serving as the storage layer for Iceberg tables and Nessie as the catalog. Accelerated 100GB data import by 50 percentage, reducing execution time from the standard 1 hour. Improved search request processing speeds by 67-83 percentage, decreasing response times from 10-15 seconds. Enhancing Resilience in Core Spring Boot Application | Improved system fault tolerance by handling Kafka downtime using a circuit breaker for graceful failure recovery. Implemented a rolling log strategy to ensure data durability and prevent payload loss during failures. Integrated Fluent Bit as a sidecar to seamlessly forward logs to AWS S3 for long-term storage and disaster recovery. Increased system fault tolerance to 99 percent, reduced data loss probability to 0.001 percent and improved log retention efficiency by 100 percent. Kubernetes Utilities Application | Engineered a Kubernetes utility tool using the Fabric8 client, achieving 100 percent API coverage for pod management and monitoring, and reducing cluster administration overhead by 30-40 percent.
VMware
|MTS-1
Summary
Screening Microservice for the Customers | Modified and refactored a Spring Boot application for customer screening based on name, email, and address, ensured all orders were captured in MongoDB before forwarding order details and party information to external screening entities. Improved the request latency upto 86 ms and 300 TPS of load. -Migrated legacy monolithic applications (20+ years old) from Tomcat servers to Kubernetes-ready images, improving scalability and portability by 60-70 percent without requiring full microservices conversion.
Education
Universitry of Petroleum and Energy Studies
Bachelors
Technology
Grade: 7.5
Skills
Languages
Java, C++, C, Shell scripting, SQL.
Developer Tools
VS Code, IntelliJ, Postman, Git Bash.
Technologies/Frameworks
SpringBoot, AWS, Apache Spark, Apache Iceberg, Kafka, RabbitMQ, Docker, Kubernetes, Mongodb, Apache Pinot, Postgres, MySQL, Git, Redis.