Quality Engineer

• Develop and execute QE methodologies for BI solutions across Enterprise Data Warehouse and Big Data platforms.
• Design and implement test plans, test cases, and automation scripts for BI dashboards, semantic models, and reporting workflows.
• Validate data accuracy, transformations, and business rules across Snowflake, Oracle, and other data sources.
• Ensure adherence to quality standards, scalability, and maintainability of BI solutions.
• Drive process improvements to enhance test coverage, reduce defects, and improve delivery timelines.
• Build and maintain automation frameworks for regression and performance testing of BI systems.
• Collaborate with BI developers and data engineers to identify defects early and ensure timely resolution.
• Provide quality metrics and reporting to stakeholders for transparency and continuous improvement.
• Support data governance and data quality initiatives, ensuring compliance with enterprise standards.
• Participate in release readiness reviews, validating deployments and ensuring production stability.

Top Requirements (Must Haves)

• 3+ years (mid-level) / 5+ years (senior) experience in Quality Engineering or QA for BI, Data Analytics, or Data Warehouse environments.
• Strong hands-on experience with MicroStrategy (MSTR) and Power BI testing, including dashboard validation and semantic layer checks.
• Proficiency in SQL for data validation and test automation; experience with Python or Unix scripting for automation frameworks.
• Familiarity with Snowflake and on-prem Oracle data sources.
• Understanding of BI best practices, relational structures, dimensional modeling, and data warehouse concepts.
• Experience with data quality checks, source system analysis, and business rule validation.
• Knowledge of Azure data pipelines and data flows for end-to-end validation.
• Strong experience in test automation, performance testing, and regression testing for BI solutions.
• Excellent communication skills for documenting test strategies, reporting defects, and collaborating with cross-functional teams.
• Ability to work independently in a fast-paced, agile environment and manage multiple priorities.
• Experience with customer data in a retail setting is preferred