QA Practice Lead - Enterprise Data Warehouse

About the role

The QA Practice Lead owns the Enterprise Data Warehouse (EDW) QA practice and is accountable for its shift-left, test-driven operating model, the service level objectives the practice commits to, and the development of the QA Leads and engineers within it. The role leads the practice end to end, including QA Leads embedded in each delivery team, automation engineers and the shared engineer pool.

Key responsibilities

• Own and continuously improve the shift-left, test-driven operating model, with QA engagement from backlog refinement, acceptance criteria and test design before code is written, and stage-by-stage QA responsibilities integrated with the delivery process.
• Define, baseline and report service level objectives such as first-pass quality rate, defect escape rate and automated regression coverage, and drive the improvement plan against them.
• Own the data quality CI/CD gate standards (accuracy, latency, performance, security) applied on every environment promotion, and the enforcement framework.
• Represent QA in service governance with US Enterprise Data stakeholders: steering committee, delivery reviews, escalations and maturity assessments.
• Plan capacity across the four delivery teams, balance the shared engineer pool against demand and manage sprint-level QA commitments.
• Set the test strategy, standards, templates and tooling for data validation, regression, source-to-target, performance and security testing across SQL Server, SSIS, dbt, Fivetran, Python ingestion and the Databricks Lakehouse.
• Own the QA knowledge base, onboarding programme and skills matrix, and run the certification and upskilling track including Databricks readiness.
• Recruit, coach, appraise and develop QA Leads and engineers, and run performance and career conversations.
• Champion responsible use of AI/LLM-powered tools (e.g. Claude, Copilot) for test design, synthetic data and query review, with validation standards for AI-assisted output before production use.
• Act as escalation point for quality risks, release readiness disputes and post-production defects, leading root cause analysis and corrective action.
• Communicate practice status, metrics and risks to leadership and US stakeholders, presenting demos, timelines and insights.