Gangireddygari JyothiSwaroop Reddy

Designed and implemented end-to-end Azure data engineering solutions to support healthcare claims processing and revenue cycle management. Architected an end-to-end data engineering pipeline for insurance claims analysis and customer segmentation. Integrated multi-source data (Rest APIs, CSV, JSON, SQL Server) into Azure Data Lake Storage (ADLS) using Azure Data Factory (ADF) for scalable data ingestion. Designed and implemented a medallion architecture (Bronze, Silver, Gold layers) to enhance data quality and enable efficient reporting. Performed advanced transformations in Azure Databricks, leveraging Delta Tables for a data lakehouse architecture. Automated pipelines to streamline data processing, improving operational efficiency by 20%. Enabled actionable insights through Power BI reporting, driving a 15% increase in targeted marketing effectiveness and reducing customer churn by 10%. Engineered a scalable data platform to process Electronic Medical Records (EMR), claims, and provider/diagnosis data. Leveraged Azure Data Factory to ingest EMR data from Azure SQL Database and flat files from external providers into a Delta Lakehouse. Standardized data processing through SCD Type 2 implementation and a common data model to maintain historical integrity across hospital branches. Built robust fact and dimension tables to support financial reporting on accounts receivable, patient demographics, and provider performance metrics. Implemented incremental data loads, reducing pipeline execution time by 30%. Enabled financial transparency and accuracy, supporting business decisions through Power BI dashboards for AR tracking, claim status, and payment trends.