The Role
The QA Lead designs testing strategies and plans, validates data accuracy, oversees BI tool testing, and leads a QA team.
Summary Generated by Built In
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
Skills Required
- 8+ years in Quality Engineering or BI/Data testing, with at least 1-2 years in a leadership or senior capacity
- Advanced proficiency in SQL
- Hands-on experience testing BI tools
- Familiarity with ETL processes and data pipelines
- Strong understanding of automation frameworks and scripting languages like Python
- Solid grasp of agile/Scrum methodologies and CI/CD pipelines
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The Company
What We Do
Concord is a technology consultancy building connected customer experiences backed by powerful AI & analytics and underpinned by secure IT foundations. Digital Experience | Data & Analytics | Engineering & Applications
