Role : ETL Test Lead Experience : 12+ years Work Mode : Offshore delivery (Hybrid/Onsite as per project needs) Primary Stack: Azure Data Factory (ADF), Azure Databricks Core Skills : Python, PySpark, Data Test Automation Strategy CI/CD : Azure DevOps Role Summary The Software Automation ETL Testing Lead owns the data testing strategy and automation approach for Azure-based data platforms.
The role requires strong hands-on expertise in Python and PySpark to define scalable validation patterns and guide teams testing large-scale analytics and AI-consumed datasets.
Experience with digital supply chain platforms is preferred but not mandatory.
Key Responsibilities Define and govern ETL testing standards, automation strategy, and best practices.
Design and standardize Python- and PySpark-based automation frameworks.
Establish validation approaches for ADF and Databricks pipelines.
Define data quality rules for analytics-ready datasets (completeness, consistency, volume, schema).
Review and approve test plans, automation design, and execution results.
Lead and mentor ETL testing engineers; conduct code reviews for automation assets.
Define and track data quality metrics and test effectiveness KPIs.
Coordinate testing across multiple releases and delivery teams.
Act as the escalation point for critical data quality or release issues.
Collaborate with Data Engineering and DevOps teams to integrate testing into Azure DevOps CI/CD.
Required Skills & Experience 12+ years of experience in ETL / Data Testing / Data Quality, including team leadership.
Strong experience with Azure Databricks and Azure Data Factory.
Expert-level Python for automation frameworks and validation utilities.
Strong PySpark expertise for validating large-scale transformations and datasets.
Advanced SQL skills for reconciliation and issue analysis.
Experience defining and enforcing data quality standards at scale.
Proven experience leading offshore or distributed teams.
Preferred (Nice to Have) Experience leading enterprise-scale data testing programs.
Exposure to digital supply chain, logistics, or operational data (preferred, not mandatory).
Experience validating high-volume, analytics-driven data platforms.
Skills: ETL Testing Pyspark Python Azure Data bricks Data factory