Priyanka Kumari

Key Responsibilities and Contributions

• End-to-End Data Ingestion
• Designed automated data pipelines to ingest large volumes of RxClaim adjudication data into Amazon S3, leveraging AWS Glue Crawlers to catalog schemas.
• Configured AWS DMS for continuous replication of on-premise databases, ensuring timely updates of claims records in the data lake.
• ETL & Data Transformation
• Developed and scheduled AWS Glue Jobs using PySpark to cleanse, enrich, and transform raw claims data into optimized Parquet files.
• Applied partitioning strategies (e.g., by date or claim type) to improve query performance and reduce costs.
• Analysis & Insight Generation
• Utilized Spark SQL to run complex joins and aggregations, uncovering trends in prescription usage, cost patterns, and seasonal fluctuations.
• Collaborated with actuarial and finance teams to create predictive models for cost forecasting, leveraging large-scale claim history.
• Visualization & Reporting
• Integrated Amazon QuickSight with S3 and Athena to build interactive dashboards tracking claim volume, cost breakdowns, and adjudication SLAs.
• Provided self-service analytics to non-technical stakeholders, reducing ad-hoc report turnaround times by 40%.
• Security & Compliance
• Ensured HIPAA and PHI compliance by encrypting S3 data at rest and restricting access via IAM policies and VPC endpoints.
• Collaborated with InfoSec teams to implement robust monitoring and logging (CloudTrail, CloudWatch), keeping a full audit trail of data access.
• Notable Achievements
• Reduced ETL runtime by 30% through optimized Spark job configurations and effective data partitioning.
• Saved 25% on storage costs by transitioning historical claim data to S3 Glacier and adopting columnar formats.
• Led a cross-functional initiative that significantly improved accuracy in claims reporting, supporting key business decisions on cost management.
  

• Designed and implemented data engineering pipeline to automate data processing tasks