Prakriti Jain

• Designed and built a Databricks ETL pipeline ingesting JSON book metadata from the OpenLibrary REST API, processing 500K+ records through automated cleaning and validation stages. • Transformed deeply nested JSON datasets using Python and PySpark, structuring them into curated Delta Lake analytical tables with enforced schema evolution. • Loaded processed datasets into Snowflake, enabling SQL-based reporting and metadata analysis for the research team’s digital humanities project.

• Built and orchestrated ETL pipelines using Apache Airflow for scheduling and dbt for transformation, reducing end-to-end runtime by 30% across pharmaceutical data workflows. • Improved data query performance by 20% by refactoring Python-based data processing scripts and optimizing MongoDB API integration layers. • Automated deployment workflows using Docker containers and CI/CD pipelines (Jenkins), increasing deployment reliability by 25% and eliminating manual release steps.

• Managed 95% on-time delivery of MIDAS/Consumer Health databases for project clients across 90+ countries. • Automated anomaly detection models for pharmaceutical data load using Python and SQL. • Applied analytical and system optimization skills to ensure 99.5% data quality and end-to-end system performance. • Performed troubleshooting and analysis on applications handling the OTCIMS database.