Rajat Aggarwal

Cognizant Technology Solutions – Gurugram, India, June 2022 – Present.

• Developed and maintained scalable ETL pipelines using Python, PySpark, and Azure Data Factory.
• Optimized PySpark applications for performance, reducing processing time by 25%.
• Automated reporting workflows using Python save 30+ hours per month.
• Implemented data validation and quality checks using SQL and Python.
• Integrated Databricks notebooks into ADF pipelines with parameterization.
• Created Logic Apps for automated pipeline status notifications.
• Participated in design and code reviews to ensure best practices.

Azure Finance CBT Project – Johnson & Johnson.

• Migrated data from on-premises SQL Server and Teradata to Azure Cloud.
• Built ETL pipelines using ADF, ADLS Gen2, and Databricks (PySpark).
• Performed data transformations and loaded results into Delta Lake.
• Created reusable datasets, linked services, and integration runtimes.
• Used ARM templates for multi-environment deployment.

• Wrote complex SQL queries for data analysis and transformation.
• Supported ETL development and gained hands-on experience with PySpark and Azure tools.
• Completed certifications in Azure Databricks and Data Factory via Udemy.