
Data Engineering professional experienced in building end-to-end pipelines (Spark, PySpark, SQL, Python). Built automation frameworks reducing manual effort by 60%, and delivered conformed datasets powering 5+ enterprise Power BI dashboards
Associate Consultant | Associate (Promoted to Associate Consultant, 06/2026)
Base Layer (Data Platform)
Architected and delivered an end-to-end data pipeline on Spark/PySpark/SQL, enabling 20+ downstream teams to consume standardized client source data, reducing redundant data-sourcing effort across teams. Built an automated Data Quality Monitoring (DQM) script to validate pipeline outputs, ensuring data accuracy across downstream consumption. Independently led client discussions to gather requirements and align on data standards, ensuring smooth cross-team adoption.
340B Data Hub
Developed a comprehensive 340B data layer feeding 5+ enterprise Power BI dashboards used across US operations, integrating Spark, SQL, SAS, and Python workflows to standardize KPI definitions and ensure consistent reporting across business personas. Served as primary point of contact for client stakeholders, translating business requirements into technical specifications and driving alignment across teams.
Ingestion Automation
Designed and developed a Python-based automation framework to auto-generate JSON and properties config files for RDRIVE-to-Consumption pipelines, cutting manual configuration effort and errors by 60%.
Completed structured training in technical initiatives, applying C++ and Python to enhance team projects in debugging and test case development.