Sowmya Nadipineni

About Sowmya Nadipineni

I’m a Software Developer with 4+ years of experience building scalable, cloud-native, and AI-driven solutions across enterprise, healthcare, and education domains. My expertise spans Java (Spring Boot, Hibernate), Python (Flask, FastAPI, Django), and full-stack development with React & TypeScript, along with strong proficiency in databases, distributed systems, and cloud platforms (AWS, GCP, Azure DevOps).At Uber, I engineered high-volume transactional systems—optimizing PostgreSQL queries to cut dashboard load times by 55%, automating CI/CD pipelines with Docker and Azure DevOps, and building microservices for authentication, payments, and analytics used by 25K+ drivers and riders monthly. Previously, I developed ETL pipelines, full-stack schedulers, and ML-driven solutions that reduced manual workflows by hours and powered decision-making at scale.I’m also passionate about AI/ML applications—from NLP pipelines with Hugging Face Transformers to CNN-based computer vision models deployed with AWS SageMaker. My goal is to design software that’s not only technically robust, but also improves user experience, scales efficiently, and drives measurable business impact. Core strengths: Backend & Full-Stack Development | Microservices | Cloud & DevOps | AI/ML Integration | Scalable System Design.

Experience

1. Software Developer

   Uber

   May 2024 — Present · NY, US

   Engineered a secure trip and payment management module using Java (Spring Boot + Hibernate) and Python (Flask), improving transaction throughput and reducing trip completion latency by 2.5 minutes.Built and deployed RESTful microservices for authentication, rider/driver profiles, and reporting workflows, scaling across 3 core mobility and delivery platforms.Designed 14+ responsive UI components with React.js and TypeScript, improving usability and navigation for monthly drivers and riders on the portal.Automated data ingestion workflows on AWS (S3, Lambda) with Docker and Azure DevOps CI/CD, reducing manual deployment effort by 6 hours per release cycle.Optimized PostgreSQL queries and indexing, cutting dashboard load times from 4.2s to under 1.8s, enhancing real-time tracking and reporting.Leveraged GitHub + GitLab workflows with branching strategies and peer reviews, reducing merge conflicts by 40% and accelerating production release readiness.Partnered with security teams to integrate JWT authentication and data encryption, ensuring compliance across all mobility and payments modules.Deployed FastAPI-based analytics services, integrated with Datadog and Grafana, enabling proactive monitoring and reducing incident detection time by 35%.Orchestrated Agile sprint planning with Jira, coordinating backend, frontend, and DevOps teams to deliver 5 major feature releases in 6 months.

Education

• University of New Haven

  Master's degree, Computer Science

• Jawaharlal Nehru Technological University, Kakinada

  Bachelor's degree, Computer Science