Big Data QA Manual (Onsite, Lahore, PKR Salary)

Requirements:

• 3-6 years of QA experience in Big Data testing, especially in Data Lake environments on Azure.
• Proficient in Azure Data Factory, Synapse Analytics, Databricks, and SQL for data validation and quality checks.
• Strong PySpark skills for data manipulation, transformation, and test script execution.
• Experience in data pipeline, ETL, and integration testing, ensuring accuracy and integrity.
• Expertise in functional, regression, performance, and system integration testing in big data environments.
• Hands-on experience with automated testing and maintaining test strategies.
• Knowledge of BDD frameworks and experience designing test cases accordingly.
• Familiarity with Jira, X-Ray, Zephyr for defect and test case management.
• Agile experience with active participation in Scrum ceremonies.
• Strong problem-solving, collaboration, and communication skills in cross-functional teams.
• Ability to multitask, manage priorities, and meet deadlines in fast-paced environments.
• Experience ensuring data quality, reliability, and performance for large-scale software products.

Responsibilities:

• Develop and execute test scripts to validate data pipelines, transformations, and integrations.
• Formulate and maintain test strategies including smoke, performance, functional, and regression testing to ensure data processing and ETL jobs meet requirements.
• Collaborate with development teams to assess changes in data workflows and update test cases to preserve data integrity.
• Design and run tests for data validation, storage, and retrieval using Azure services like Data Lake, Synapse, and Data Factory, adhering to industry standards.
• Continuously enhance automated tests as new features are developed, ensuring timely delivery per defined quality standards.
• Participate in data reconciliation and verify Data Quality frameworks to maintain data accuracy, completeness, and consistency across the platform.
• Share knowledge and best practices by collaborating with business analysts and technology teams to document testing processes and findings.
• Communicate testing progress effectively with stakeholders, highlighting issues or blockers, and ensuring alignment with business objectives.
• Maintain a comprehensive understanding of the Azure Data Lake platform's data landscape to ensure thorough testing coverage.