Developed an e-learning website from scratch using CSS, HTML, JavaScript, JSX, and ReactJS for the frontend.Implemented backend services using Python, Django REST Framework, Docker, Redis for caching, Elasticsearch for search engine functionality, and machine learning for the recommendation system.Deployed the project using various AWS services, including AWS Amplify, ECS (Fargate), ECR, S3, Glacier, Route 53, RDS, CloudWatch, and X-Ray.Established a CI/CD pipeline for both frontend and backend, ensuring best practices such as auto rollback, auto-scaling, and robust security measures.Utilized AWS Elemental Media Converter for transcoding and HLS streaming, and AWS VPC to deploy development and production servers in an isolated environment.

Identified, designed, and implemented internal process improvements by automating manual processes, optimizing data delivery, and re-designing infrastructure in Amazon Web Services for greater scalability.Developed a recommendation system in AWS platforms and best practices, building tools to identify common usage patterns.Built data prediction infrastructure required for optimal data extraction, transformation, and loading from different AWS sources.Collaborated with cross-functional teams to enhance data reliability, efficiency, and quality through data analytics process reviews and recommended practices in AWS.Successfully deployed recommendation systems in various environments using AWS services, including Amazon S3, EC2, Lambda, SNS, Kinesis, DynamoDB, and more.