Atul Sairani

At PwC, I lead cross-functional QA and data testing teams of 6–15 engineers for large-scale P&C insurance data transformation, data warehouse, and data lake programs. I partner with client IT and engineering leaders to align test strategy, governance, and release readiness.

I've led end-to-end ETL/ELT testing across AWS Redshift and Azure Databricks, covering ingestion, transformation, lineage, security, and reporting layers. By building Python-based automation integrated with CI/CD, I improved testing efficiency by 40%, reduced defect turnaround by 25%, and saved approximately 1,200 manual testing hours in a single release.

Before PwC, I built customer and internal chatbots at Verizon India using Google Dialogflow ES, Slack, Python, and IBM Watson Explorer. My Python modules saved an estimated 1,800 hours of manual work, while my search and autocomplete work included XSLT development and a linear regression model.

My development foundation comes from Cognizant, where I led developers, built MarkLogic and REST integrations, strengthened API and XML testing, and delivered reliable releases. I bring hands-on SQL, Python, automation, cloud data, and stakeholder leadership to data quality challenges.