• Designed 10+ HIPAA-compliant RESTful APIs using FastAPI, securing 35,000+ patient records across 20+ clinics through JWT authentication and role-based access control; achieved zero breaches with high system availability.

• Created responsive patient dashboard (React, TypeScript, Material-UI) with real-time Chart.js visualizations; slashed API latency 25% through Vite-optimized Axios calls, supporting 1,000+ concurrent users.

• Streamlined clinical analytics pipeline for 35,000+ patient records using Pandas/NumPy; implemented EWMA for anomaly detection, triggering alerts and cutting analysis time by 60%.

• Built a KPI microservice delivering sub-200ms queries for 100+ clinical staff, lowering HR review time by 60% & enabling data-driven staffing decisions.

• Automated cell nucleus analysis using OpenCV, transforming 10,000+ microscopy images into structured datasets by quantifying size, shape, and texture metrics, slashing manual analysis time by 60%.

• Built a Python-based ETL pipeline (Pandas, SQL) to integrate fragmented datasets from 3 sources into a centralized data warehouse, reducing data preparation time by 50% and enabling cross-dataset analysis for actionable insights.

• Conducted EDA to identify trends in cell behavior, delivering actionable insights via Power BI dashboards that boosted team productivity by 30%.

• Developed & deployed secure backend microservices with Oracle Cloud (OCI), REST APIs (Maven, Hibernate, Spring, SQL), supporting systems that processed up to a million API requests per day across 1000 hospitals.

• Built monitoring dashboards for microservices on OCI using Prometheus, Grafana, and AlertManager, cutting response times by 6 hours, resulting in annual cost savings of $35,000.

• Created Python tooling to integrate Zabbix alerts with Jira API, auto-generating incident tickets & reducing manual effort by 70%, and alert backlog by 40%.

• Optimized AWS S3 usage cost via lifecycle policies and deduplication, cutting storage costs by 35% and saving $100K+/year for an EHR analytics platform.

• Led AWS cloud migration leveraging Python and Terraform to migrate 2,300+ on-prem servers to AWS, enabling real-time ETL of 50+ TB/day healthcare data and reducing deployment time by 55%.

• Partnered with the DevOps team to automate CI/CD pipelines using Docker, Kubernetes, GitLab (bash scripts) and Jenkins, shortening release cycles by 50% while boosting code quality by 60%

• Automated database migrations with Python scripts, streamlining JDBC string updates and reducing manual effort from 700 to 60 hours per year.

• Migrated client’s on-prem infrastructure to a scalable OpenStack environment using Chef for automated provisioning, cutting infrastructure costs by 25%.