Data Quality Business Partner
This is your opportunity to join AXIS Capital – a trusted global provider of specialty lines insurance and reinsurance. We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture. As a member of AXIS, you join a team that is among the best in the industry. At AXIS, we believe that we are only as strong as our people. We strive to create an inclusive and welcoming culture where employees of all backgrounds and from all walks of life feel comfortable and empowered to be themselves. This means that we bring our whole selves to work. All qualified applicants will receive consideration for employment without regard to race, color, religion or creed, sex, pregnancy, sexual orientation, gender identity or expression, national origin or ancestry, citizenship, physical or mental disability, age, marital status, civil union status, family or parental status, or any other characteristic protected by law. Accommodation is available upon request for candidates taking part in the selection process. Data Quality Business Partner Job Family Grouping: Data & Analytics Job Family: Data Quality How does this role contribute to our collective success? As a Data Quality Business Partner within AXIS, you will support the Data & Analytics Transformation programme, which aims to replace our legacy data estate and modernise it through a new data platform. Your role will focus on helping ensure the integrity, accuracy, and usability of data across the organisation. Working closely with technical teams and business stakeholders, you will apply data quality best practices and contribute to embedding them into operational workflows and strategic decision-making. What will you do in this role?
- Business Partnering and Stakeholder Engagement
- Collaborate with business stakeholders (e.g. underwriting, claims, actuarial, finance) to understand data quality needs and pain points, acting as a liaison between business units and the data quality team to ensure alignment and address challenges.
- Translate business requirements into data quality rules and validation checks.
- Collaborate with data stewards, analysts, engineers, and governance teams to ensure alignment on data quality goals.
- Asist in workshops and training sessions to raise awareness of data quality issues.
- Contribute to cross-functional projects by supporting data quality activities and providing input based on established practices.
- Data Quality Management
- Execute routine monitoring and assessment of data quality across core insurance systems (e.g. policy, claims, underwriting, exposure management, pricing).
- Prepare dashboards and reports to support data quality performance tracking.
- Identify data anomalies and work with relevant teams to resolve root causes and recommend corrective actions.
- Conduct data profiling and analysis to identify trends, gaps, and improvement opportunities, with direction from senior colleagues.
- Collaborate with technical teams and business stakeholders to support the application of data quality standards in operational processes.
- Process Improvement
- Participate in regular reviews with stakeholders to support process refinement based on data insights.
- Implement data quality checks into existing business processes (e.g., onboarding, reporting, compliance).
- Support efforts to automate data cleansing and enrichment processes as directed.
- Ensure that system upgrades or migrations include data quality considerations.
- Contribute to the design and testing of new systems and data pipelines by following detailed guidance and specifications.
- Experience in data quality, data analysis, or data governance within the insurance sector.
- Understanding of insurance operations and data flows (e.g. policy lifecycle, claims processing).
- Working knowledge in SQL, Excel, and data visualization tools (e.g. Power BI, Tableau).
- Familiarity with data quality and data governance tools and frameworks (e.g. DQPro, Soda, DDW).
- Strong communication and stakeholder management skills.
- Analytical mindset with attention to detail and willingness to learn and solve problems.