• Ensure high-quality delivery across complex customer programmes. • Provide end-to-end test leadership. • Act as Programme Test Manager on large or complex initiatives. • Own the programme test strategy and oversee quality gates and assurance activities. • Produce and maintain all key test artefacts, ensuring testing is carried out to robust, agreed standards throughout the lifecycle.

• Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains. • Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps. • Execute structured acceptance testing for each pipeline prior to promotion to production environments. • Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives. • Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance. • Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve.

• Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains. • Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps. • Execute structured acceptance testing for each pipeline prior to promotion to production environments. • Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives. • Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance. • Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve.

• Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains. • Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps. • Execute structured acceptance testing for each pipeline prior to promotion to production environments. • Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives. • Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance. • Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve.