Job description

Main Activities: - Test Planning & Execution: Design detailed test strategies/plans, test cases, and test scripts to validate data accuracy, integrity, and system functionality in ETL pipelines, including both functional and non-functional testing. - Data Quality: Collaborate with data engineers to monitor and ensure the accuracy, completeness, and consistency of data across various data platforms, validating transformations and data integrity in the ETL pipelines, identifying potential data issues and ensuring proper data validation. - Data Pipeline Testing: Collaborate with data engineering teams to design and execute tests for Data pipelines running on Azure Fabric. Ensure data transformation, integration, and storage processes are functioning as expected. - SQL Database Testing: Development and execution of SQL-based automated tests for database validation, ensuring data integrity, performance, and security across multiple databases - Performance Testing: Conduct performance testing to evaluate the scalability, stability, and performance of large-scale data systems. - Automated Testing: Develop and maintain automated test frameworks for data applications, including ETL processes, APIs, and data integration systems, using industry-standard tools. - Defect Tracking & Resolution: Work with development and operations teams to identify, report, and track defects, ensuring timely resolution of issues. - Continuous Improvement: Propose and implement improvements to testing processes and frameworks to increase the efficiency and effectiveness of the quality assurance efforts. - Collaboration: Partner with business stakeholders, project managers, and technical teams to ensure alignment with quality goals and deliverables. - Mentorship: Provide guidance and mentorship to junior quality engineers, helping them improve their technical skills and understanding of quality engineering best practices. - Compliance & Best Practices: Ensure adherence to industry standards and best practices related to software quality, particularly in relation to data systems, ETL processes, and cloud technologies. Knowledge/Skill Requirements: - 7+ years of experience in software quality engineering, with at least 3 years of experience in an enterprise data environment. - Proven experience in automated testing tools (e.g., Pytest/DBT/ETL automation tools and API automation tool) - Hands-on experience with ETL automation tools, including DBT, Airflow, or equivalent platforms. - In-depth knowledge of data management, data warehousing, data lakes, and cloud-based ETL/integration workflows. - Experience with event-driven data streaming platforms (e.g., Kafka, Event Hubs, or similar). - Proficient in SQL and scripting languages like Python for test automation and data validation. - Experience with Microsoft Fabric is preferred. - Proficient in scripting languages (e.g., Python, Java, SQL) for test automation and ETL process validation. - Experience working with Azure Data Factory, Azure Synapse Analytics, or other Azure-based ETL and data integration tools. - Strong knowledge of software development methodologies (Agile, Scrum, Waterfall) and experience in a continuous integration/continuous deployment (CI/CD) environment. - Familiarity with version control systems (e.g., Git), CI/CD tools (e.g., Jenkins, Azure DevOps), and cloud infrastructure (e.g., Azure).Certifications/Additional Training – Nice-to-Have: - A relevant certification (e.g., ISTQB) is a plus. - Experience working with data governance tools such as Azure Purview and ensuring data compliance. - Relevant certifications (e.g., Azure DevOps, Azure ML, ISTQB) are a plus.

Requirements