Rupal User

As a Data Engineer II, I implemented a RAG application using LangChain and Llama Index, leading to a significant increase in customer engagement and sales. I also optimized profitability through big data processing on Azure and automated data analytics pipelines using Terraform, enhancing efficiency for multiple clients.

Led the implementation of a Profit Optimization Platform on Azure, utilizing PySpark and Azure Synapse Analytics to significantly reduce execution time for data processing. This resulted in a substantial increase in profitability for the company.

Developed a Data Platform Automation System using Terraform, enabling infrastructure-as-code adoption and reducing analytics pipeline setup time for clients. Conducted training for over 60 engineers on cloud data pipeline customization.

Implemented a Patient Portal System using Spark and Terraform, processing various data formats and integrating with AWS Glue. Developed a streaming system for sensor data to alert on abnormal readings, significantly enhancing patient data management.

Led a data engineering project to create a Data Powered Marketing Insights Platform, focusing on customer retention and churn prevention, resulting in a significant financial impact.

Built a Big Data Pipeline for an Underwriting Application using Spark and Databricks, optimizing complex computations and increasing revenue significantly. Established data quality rules and orchestrated pipelines using Airflow.

Grade: 4.0

Major in Computer Science with specialization in Machine Learning. Graduate projects included multi-task learning using custom CNN to detect text in images and videos, hospital readmission prediction using NLP, AI agents for game play optimization, and a full-stack web application to find women STEM mentors. Coursework covered data structures and algorithms, big data, and Artificial Intelligence.