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• Backend development utilizing Java, Spring Boot, using Agile methodologies and Test-Driven Development.• Load balanced using Nginx to distribute traffic requests across servers for 100% availability.• Built a real-time ETL pipeline for image streaming by utilizing AWS S3, Dask (Distributed computing), NumPy thereby reducing visualization load time by 50 seconds and cutting client meeting durations by 50% • Standardized, transformed volumetric images, to multi-scale images using SciPy, OpenCV (dataset size -100GB-2TB)• Carnegie Mellon University project - Implemented new models, views, apps using Python, React, Django, and SQLite3, which helped over 1000+ researchers generate DOIs and publish research data, saving 45 minutes per session• Automated CI/CD(Dev-ops) pipeline using GitHub actions(plugins), Docker which reduced 30% deployment time.

CAFEE (Center for Alternaive Fuels Engines and Emissions) • United States Department of Energy project – Engineered a serverless, scalable fleet management application using React, Python, AWS (DynamoDB, Lambda, API Gateway, S3, SNS, CloudWatch, CloudFormation, IAM, Cognito, boto3)• Integrated an ETL pipeline using Python, Pandas, boto3, SQL, to analyze telemetry and maintenance data for 2000+ trucks (500k+ records), reducing work hours by 80% and saving $50k in labor costs.• Collaborated with cross-functional teams, including AI scientists, PM, and engineers for project deliverables.• Managed (CSV, MATLAB) datasets using Redis for in-memory caching of frequently used telemetry data.• Improved decision-making by 50% using PowerBI, Plotly for visualizing (Diesel, Electric, Alternative Fuel vehicle data).