Designed and optimized distributed event-driven services using Python and Elixir , leveraging

concurrency primitives and supervision-tree-inspired retries for fault-tolerant execution.

Enhanced SQL and API layer performance, reducing request latency by 30% through caching,

indexing, and query optimization

Developed API-based integrations between on-premise systems and GCP services using Python

requests, REST APIs, and service accounts for secure data flow

Developed RESTful and GraphQL APIs , built integration pipelines for multi-source data using Spark,

Kafka, and Hadoop , accelerating analytics and ML workloads for customer-facing applications

Developed an e-commerce website with Java Spring Boot, Spring JPA, and Rest API for the backend, and utilized React for frontend development. Managed data using MySQL database.

Built scalable microservices with Kubernetes networking, ingress controllers, and service

discovery

Streamlined Java migration tool to reduce data migration time from Auth database to Workspace

database by 50%, resulting in improved efficiency

Built task scheduling frameworks leveraging Spark DAGs and orchestration , supporting ML data

preparation and model deployment in cloud environments

Partnered with data science teams to productionize ML pipelines, supporting AI-powered

recommendation and analytics use cases

Developed scalable data processing engines using Apache Spark, Kafka, and Python, integrating

time-series and NoSQL datasets from distributed cloud sources (AWS)

Enhanced and extended of ETL processes and data pipelines with well over 30 GB daily dataingestion rates, dealt with batch and streaming data models on Informatica and Airflow platforms

Developed and executed automation test cases for microservices-based applications using Java, Selenium, and

REST API testing, improving regression coverage by 40%.

• Implemented CI/CD-triggered test execution pipelines using Jenkins and GitHub Actions, enabling automated

smoke, sanity, and regression testing.

• Performed system and integration testing for containerized services deployed on Docker and Kubernetes,

validating service communication, data flow, and fault tolerance.

• Validated distributed transaction consistency across microservices using correlation IDs and trace-based testing.