BI QA Lead

• Strategy & Planning: Design comprehensive testing strategies test plans and test cases tailored for complex data ecosystems and ETL architectures.
• Data Validation: Validate end-to-end data accuracy from source systems to target databases data warehouses and visualization layers.
• BI Testing: Oversee the validation of analytics metrics and KPI visualizations in BI tools like Power BI Tableau or Looker.
• Automation: Lead the development and maintenance of automated testing frameworks for API validations data consistency checks and ETL workflows (e.g. using Python Playwright or Selenium).
• Team Leadership: Mentor manage and coach junior QA engineers and SDETs defining performance metrics and evaluating release readiness.
• Defect Management: Act as the primary escalation point for data anomalies logic defects and system integration issues ensuring resolution prior to production.
• Collaboration: Partner with Data Engineers Product Managers and Business Analysts to clarify acceptance criteria and ensure shift-left data quality.

• Experience: 8 years in Quality Engineering or BI/Data testing with at least 1-2 years in a leadership or senior capacity.
• SQL & Data Skills: Advanced proficiency in writing and executing SQL queries to profile compare and validate large volumes of data across various sources.
• BI Tooling: Hands-on experience testing BI tools (e.g. Tableau Power BI) and understanding of data modeling (star schemas dimensional models).
• ETL Testing: Familiarity with ETL processes data pipelines and workflow orchestration tools (e.g. Apache Airflow dbt).
• Automation & Scripting: Strong understanding of automation frameworks and scripting languages like Python is desirable.
• Methodologies: Solid grasp of agile/Scrum methodologies and continuous integration/continuous deployment (CI/CD) pipelines.

• Bachelors degree in Computer Science Information Technology Data Analytics or a closely related technical field

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