At Cardinal Health, I build and maintain GCP pipelines for pharmacy, inventory, and logistics data. My batch and streaming pipelines maintain 99.8% reliability, and I optimized BigQuery models to improve complex query performance by 47%.
I also developed Python ETL automation to validate and transform incoming data, reducing manual effort by 38%. I manage Cloud Composer workflows and apply lineage, audit logging, and PII masking to regulated healthcare datasets.
At Cognizant, I designed a data lake for policy and claims data and built Spark ETL pipelines for insurance records. I also developed Kafka ingestion and dimensional models for insurer analytics, while improving Hive query performance by about 40%.
At Deloitte, I built Azure data pipelines and PySpark transformations for banking data, including fraud monitoring and credit risk analytics. I used Delta Lake and Azure Synapse models, and optimized Spark workloads to reduce average ETL processing time by about 60%.
