2 of 2 Permanent Data Lineage Jobs in the Thames Valley

A successful and established London Market syndicate is seeking a highly motivated and detail-oriented Data Quality Analyst to join their team. The Data Quality Analyst is integral to ensuring the organization's data assets are managed, secured, and utilized to support business decision-making. As Data Quality Analyst will play a key role in maintaining … and driving quality standards, policies, and procedures related to data governance while collaborating with stakeholders across departments to enhance data quality and integrity. NB: If you do not have experience of working in the insurance sector, you will unfortunately NOT be eligible for this role. Key Responsibilities: Develop and implement a comprehensive data governance framework Help create … implement, and maintain data governance policies and procedures to ensure the business is compliant with relevant regulatory requirements Work with data owners and data stewards to establish and enforce data quality metrics, monitoring, and improvement processes Identify and appoint data stewards, providing guidance and support Develop and maintain a data catalog, taxonomy, and data More ❯

ambiguity into crisp, testable requirements. You’ll will run discovery, shape target processes, and convert value cases into stories that ship. Work shoulder-to-shoulder with Enterprise Architecture and Data/Integration leads to land AI-ready, integration-safe delivery. You will need excellent stakeholder management and engagement abilities. Reduced integration lead time and defect leakage Higher adoption of … released capabilities (self-serve dashboards, workflows) Faster cycle time from discovery to release, with clean UAT pass rates Documented data quality and lineage improvements tied to decisions Stakeholder interviews, workshops, and as-is/to-be process mapping with clear value hypotheses. Write high-quality epics, user stories, and acceptance criteria; maintain a transparent backlog and sprint flow … Jira/ADO). Define integration readiness (contracts, data classes, non-functionals) and partner with architects on patterns and guardrails. Own UAT strategy and acceptance: trace requirements → test cases → sign-off; manage defect triage and closure. Land AI-aware use cases (e.g., onboarding orchestration, payroll variance triage): clarify prompts, guardrails, and HITL checkpoints. Stand up metrics that matter (adoption More ❯