Raghuram Chandrala

About

Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.

Key Strengths

• Built end-to-end document processing/workflow platform (Angular + Spring Boot microservices + Python/Flask)
• Designed scalable async processing using Celery + RabbitMQ to keep APIs non-blocking under heavy workloads
• Cross-language microservice integration (Java + Python) with clear API contracts and schema validation
• Cloud-native deployment on AWS (Docker on ECS, auto-scaling, CloudWatch monitoring)
• Data architecture for large files using PostgreSQL (indexing/JSONB) and S3 storage
• Strong API design discipline (OpenAPI/Swagger, validation, logging, unit/integration tests, CI/CD)
• Designed Flask backend modularization using blueprints for maintainability
• Offloaded heavy file compression/processing (200–300MB files) to background workers to prevent timeouts
• Implemented RabbitMQ-based job queuing to improve API responsiveness
• Optimized data comparison using Pandas batch processing to reduce memory usage
• Improved concurrency/scalability with Gunicorn multi-worker setup
• SQLAlchemy/PostgreSQL performance tuning with indexing and EXPLAIN ANALYZE
• Avoided N+1 query issues using joinedload/selectinload
• Implemented multi-tenant data isolation (separate schemas vs shared tables with tenant filtering)
• Delivered measurable performance gains: API response time ~30s to <1s; reduced DB load ~50%; increased throughput

Experience

Skills

Languages