Data QA Practice Lead
Salary: ₱140,000 – ₱150,000 per month
About the role
Lead the Enterprise Data Warehouse (EDW) QA practice end to end. You will be accountable for the shift-left, test-driven operating model, the service level objectives the practice commits to, and the development of the QA Leads and engineers in the practice. You will report to the VP, Quality.
Key responsibilities
Lead the EDW QA practice end to end, including the QA Leads embedded in each delivery team, the automation engineers, and the shared engineer pool
Own and continuously improve the shift-left, test-driven operating model: QA engagement from backlog refinement, acceptance criteria and test design agreed before code is written, and stage-by-stage QA responsibilities integrated with the Enhancement Team delivery process
Define, baseline and report the practice service level objectives, including 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 framework used to enforce them
Represent QA in the service governance cadence 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; run the certification and upskilling track including Databricks readiness
Recruit, coach, appraise and develop QA Leads and engineers; 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 use in production test cycles
About you
10+ years in software or data quality assurance, with 4+ years leading QA teams in a data engineering or data warehousing environment
Proven track record establishing or transforming a QA practice, including shift-left or test-driven approaches and QA embedded in agile delivery teams
Hands-on background in data testing with SQL and Python; able to review test designs and queries and challenge test coverage credibly
Experience defining and reporting quality metrics and service level objectives to senior stakeholders
Experience running QA in a managed service or shared service model with cross-border stakeholders
Strong people leadership: hiring, coaching, performance management and succession planning
Excellent verbal and written communication, including the ability to present to executive and non-technical audiences
Familiarity with Agile/Scrum delivery and with Azure DevOps or equivalent work management tooling
Bachelor's Degree in Computer Science, Information Systems, Computer Engineering or related field