QE Automation Lead

As QE Automation Lead, you own the automation strategy for data testing within a multi‑vendor data transformation programme. You lead a team of SDETs, shaping and delivering an AI‑augmented automation framework for AWS data platforms and end‑to‑end data validation. You partner with the QE Lead to drive quality, governance and auditable test results across multiple delivery teams. This role blends hands‑on technical contribution with strategic leadership to deliver high‑quality data solutions at scale.

• flexible work options
• learning and development opportunities
• wellbeing support
• diversity and inclusion commitment
• career growth
• competitive benefits

• Lead and manage the Automation Test Engineers (SDETs) for data testing across multiple delivery teams
• Own automation scope, backlog and priorities aligned to programme plans
• Design and implement automated data testing strategy and frameworks
• Hands‑on development of automated test scripts, data validation logic and AI utilities
• Lead testing of AWS Lakehouse/data pipelines (AWS Glue, Iceberg, data platforms)
• Ensure auditable test coverage across unit, system, E2E, performance and data validation
• Provide dashboards/reports on test progress, defect trends and quality risks
• Collaborate with Data Engineers, Platform Engineers, Product Owners and partners to align testing solutions
• Integrate automated tests into CI/CD pipelines (GitHub Actions, etc.)
• Guide test data management including synthetic data and masking and environment readiness
• Support Test Exit/Go‑Live readiness decisions and QA reviews
• Champion quality standards and test governance within the scrum/value stream
• Act as a technical quality authority within delivery teams

• Experienced Test Lead/Automation Lead for QE teams in large data transformation programmes
• Hands‑on expertise in building scalable automated data testing frameworks with reconciliation/validation logic
• Proficient in Python/PySpark, SQL, Oracle, HDFS and YAML
• Experience with AWS data pipelines, AWS Glue, data lakehouse/warehouse concepts
• Knowledge of AI‑driven testing solutions and accelerators
• Strong OO programming foundation (JavaScript/TypeScript, Java, C#, Python)
• Experience with test plans for functional and non‑functional data testing
• Excellent communication to translate technical concepts to diverse stakeholders
• Familiarity with test tools (JIRA, XRAY, ADO) and CI/CD integration
• Data environment testing focus including data quality, data validation and testing environments

• leadership and coaching
• clear communication
• problem‑solving
• Python/PySpark
• SQL
• AWS Glue