BI QA Lead

• *Key Responsibilities**

• **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.

• *Essential Qualifications*** **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.

• *Common Educational Background*** Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a closely related technical field

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