• Designed and developed scalable RESTful APIs using Python, FastAPI, and Flask, enabling enterprise applications to securely process and exchange over

1.2M API requests per day, improving system interoperability across distributed services.

• Built backend microservices integrated with PostgreSQL and Redis caching layers, optimizing data retrieval performance and reducing API response latency

by 32%, improving overall application responsiveness for high-volume users.

• Developed asynchronous backend processing workflows using Celery and RabbitMQ, automating background tasks including data processing and report

generation, reducing manual operational workload by 40%.

• Implemented cloud-native backend services on AWS using EC2, S3, and RDS, enabling scalable infrastructure deployments and improving application

availability to 99.8% uptime across multiple production environments.

• Optimized database queries and indexing strategies in PostgreSQL, reducing query execution times by 28% and improving performance for transactional

systems handling large datasets.

• Collaborated with frontend teams to integrate backend APIs with React-based client applications, ensuring seamless API consumption and improving feature

delivery cycles by 25% across agile development sprints.

• Implemented automated CI/CD pipelines using Jenkins and GitHub Actions, enabling faster build and deployment cycles while reducing deployment errors

by 35% across staging and production environments.

• Contributed to backend service development with increasing ownership by designing and delivering production-ready modules independently, improving

feature delivery speed and supporting scalable system architecture initiatives within the engineering team.

• Developed backend services using Python, Django, and Flask, building scalable APIs supporting enterprise applications used by more than 80K active users,

improving backend service reliability and system scalability.

• Designed and implemented microservices architecture for backend modules, enabling independent service deployments and improving system

maintainability while reducing overall application downtime by 20%.

• Built data processing pipelines using Python, Pandas, and SQL, enabling automated ingestion and transformation of large datasets, improving reporting and

analytics performance across internal business systems.

• Implemented secure authentication mechanisms using OAuth2 and JWT tokens, strengthening API security and protecting sensitive application data in

compliance with enterprise security standards.

• Developed backend integrations with MongoDB and PostgreSQL databases, designing optimized data models and indexing strategies that improved query

performance by 30% for large transactional datasets.

• Integrated Kafka messaging systems to enable event-driven communication between microservices, improving system scalability and reducing synchronous

processing bottlenecks across backend workflows.

• Implemented automated testing frameworks using PyTest and unit testing practices, increasing code coverage to 85% and reducing production defects

through continuous quality assurance practices.

• Collaborated with DevOps teams to containerize backend applications using Docker and Kubernetes, enabling scalable cloud deployments and improving

infrastructure provisioning efficiency across multiple environments.