Anil Gaikwad

Designed and developed scalable microservices with FastAPI, achieving a 30% improvement in backend performance and faster API responses. Implemented Celery for asynchronous task processing, enhancing resource utilization and increasing system performance by 40%. Architected event-driven architectures leveraging AWS DynamoDB Streams, reducing API response times from 500 ms to 350 ms and accelerating data load times from 2 seconds to milliseconds. Orchestrated scalable data pipelines with AWS Batch, Lambda, DynamoDB Streams, and Celery to power real-time analytics and AI-driven insights. Created a modular survey question management system using Factory and Strategy design patterns, cutting development time by 25% and improving maintainability.

Migrated serverless functions to Python FastAPI, cutting backend latency from 3 seconds to under 1 second and improving scalability. Streamlined real-time user feedback collection for diary studies by integrating AWS Batch with WebSocket, reducing media upload times by 40% using Amazon S3 Accelerate and multipart uploads. Enhanced high-traffic APIs with pagination, caching, async processing, and improved OpenSearch/DB queries, reducing API latency from 2s to 300 ms. Worked closely with cross-functional teams to define API contracts, reducing integration time by 20%.

Designed and built RESTful APIs using Python and Flask, improving system performance by 30% and reducing average response time from 1.4 seconds to 800 ms. Optimized MySQL queries, reducing execution time by 20%, improving dashboard load speed and data retrieval efficiency. Cooperated with a 4-member team to ensure smooth frontend-backend integration, reducing API failure rates.