Description

You will own end-to-end ETL testing across complex data pipelines, ensuring data integrity, quality, and seamless integration across multiple systems.

This role is hybrid.

Responsibilities

• Perform end-to-end ETL testing, validating data extraction, transformation, and loading processes for accuracy and consistency.
• Design and execute test strategies, including functional, integration, and regression testing, with a focus on risk-based coverage.
• Develop and maintain ETL automation frameworks using Python, PySpark, and Pandas to build reusable validation scripts and improve coverage.
• Write and execute complex SQL queries for backend validation, data reconciliation, and root cause analysis of data-related defects.
• Validate BI dashboards, reports, and KPIs, ensuring data consistency between source systems and reporting layers.

Required Skills

• 8+ years of experience in ETL testing, Big Data testing, and manual testing.
• Strong expertise in data validation, data reconciliation, and end-to-end testing of complex data pipelines.
• Proficiency in Python, PySpark, and Pandas for building test automation frameworks and utilities.
• Advanced SQL skills for backend data validation, query optimization, and complex joins/aggregations.
• Experience with Azure cloud data technologies, including Azure Data Factory (ADF), Azure Databricks, and Azure Data Lake Gen2.
• Hands-on experience with Azure DevOps for test tracking and CI/CD integration.
• Ability to analyze business requirements and convert them into comprehensive test scenarios and cases.
• Experience in defect management, including identification, logging, prioritization, and tracking.

Preferred Skills

• API testing experience using tools such as Postman.
• Exposure to automation best practices and CI/CD environments.

Key Skills

Education

Bachelor's or Master's degrees