• Conducted end-to-end SDLC processes, including requirement analysis, development, testing, and deployment, to deliver reliable and compliant healthcare data solutions in an Agile environment. • Leveraged Python with libraries like NumPy, Pandas, and Matplotlib to perform data cleaning, wrangling, and visualization, improving the accuracy and interpretation of healthcare datasets. • Designed and developed over 25 dashboards using Tableau and Advanced Excel, delivering actionable insights that improved stakeholder decision-making and increased operational efficiency by 30%. • Completed 100% compliance with HIPAA and HITECH rules, while aligning data processes with Medicaid and Medicare payment models, ensuring regulatory adherence across all healthcare systems. • Implemented healthcare terminologies and interoperability standards, streamlining EHR integration and improving data consistency across systems by 40%, enhancing overall data reliability. • Conducted API testing and application integration using Open MRS and Postman, ensuring seamless communication between healthcare applications and reducing integration errors by 25%. • Exploited SQL and PostgreSQL for querying, managing, and analyzing large-scale healthcare data, ensuring efficient data storage and retrieval for compliance reporting.

The interview process consisted of a 20–30 minute AI-based assessment where I responded to a series of pre-recorded questions. Each question allowed a short preparation time followed by a timed response, during which my voice and screen activity were recorded. The format focused on evaluating my communication skills, problem-solving approach, and technical knowledge in a structured, self-paced environment.