Support the data governance framework, contributing to the strategy and processes to continually elevate the quality, integrity and accuracy of our data assets. Collaborate with business stakeholders to maintain artefacts supporting understanding of our data. About Canopius Canopius is a global specialty lines (re)insurer. We are one of the leading insurers in the Lloyd's of London insurance market with offices in the UK, US, Singapore, Australia and Bermuda. At Canopius we foster a distinctive, positive culture which enables us to bring our whole selves to work to flourish as people, and build a business which delivers profitable, sustainable results. Based in incredible new offices in the heart of the City of London, Canopius operates a flexible, hybrid working model and is committed to providing an environment that challenges employees to be their best and where everyone's unique contributions are recognised, valued and respected. We are fully committed to equal employment opportunities for all applicants and providing employees with a work environment free of discrimination and harassment. All employment decisions are made regardless of age, sex, gender identity, ethnicity, disability, sexual orientation, socio-economic background, religion or beliefs, marital or caring status, or any other status protected by the laws or regulations in the locations where we operate. We encourage and welcome applicants from all diverse backgrounds. We make reasonable adjustments throughout the recruitment process and during employment. Please let us know if you require any information in an alternate format or any other reasonable adjustments. The Data Governance and Data Quality team ensures that data throughout Canopius remains accurate, reliable, and fit for purpose. This is achieved by proactively monitoring data quality and addressing data exceptions as they arise. As a centralised function, the team serves as the main point of contact for reporting data quality queries, carrying out root cause analyses on issues identified, whether related to data entry, process, system, or reporting concerns, and collaborating with data owners, stewards, or custodians to resolve problems and establish robust data quality checks. The team runs regular working group meetings with representatives from each business domain, including data owners, stewards, and custodians. These meetings provide a transparent forum for discussing and resolving data-related issues, fostering a culture that values and promotes data quality across Canopius. Discussions focus on prioritising data quality queries, reviewing raised items, tracking progress on outstanding issues, and ensuring accountability for follow-up actions. This role requires strong analytical and stakeholder management skills. The successful candidate will be expected to conduct thorough root cause analyses, clearly communicate the nature and impact of data issues, identify the appropriate stakeholders for remediation, and lead working group sessions. Additionally, the role involves developing data quality rules that align with established data standards and business requirements. Responsibilities will include: Support the implementation and monitoring of data quality processes to ensure that organisational data is accurate, complete, timely, and fit for purpose. Undertake investigation and analysis of data quality issues as they are reported to identify and document the impact, the associated risk(s), the root cause(s), potential remediation options and preventative actions / controls that should be put in place to prevent recurrence. Liaise with data stewards in defining data quality standards, determining how they will be applied across the business, and implementing them as rules within the data quality software. Prepare presentation materials and lead data quality working group sessions. Monitor the performance of the data quality software. Support the development of data quality checks in the data quality software. Train business teams on the data quality software Facilitate business user sessions to evaluate data quality rules and exception KPIs, ensuring that exception rules function as intended and that additional controls are developed in accordance with business needs. Skills and experience: Excellent analytical and problem solving skills. Strong Excel and data analysis skills. Strong SQL skills to analyse and manipulate data. Strong communication and stakeholder management skills. Knowledge of best practices in data quality analysis. Insurance Market domain knowledge is required. Power BI and Databricks knowledge is desirable. This will include the competencies Stakeholder engagement: Acts as a central point of contact for data quality queries, working closely with data owners, stewards, custodians, and business teams to communicate issues, agree remediation actions, and ensure accountability for resolution. Collaboration and teamwork: Collaborates with representatives from multiple business domains through regular working groups, facilitating discussion, prioritisation, and joint ownership of data quality issues and actions. Adapting to change: Responds to emerging data quality issues as they arise, adjusting focus and approach based on reported exceptions, changing priorities, and business needs. Continuous Improvement: Implements, monitors, and enhances data quality processes, rules, and checks by analysing root causes, defining preventative controls, and aligning data quality standards to business requirements. Innovation: Develops and implements data quality rules and exception checks within data quality software to improve the accuracy, reliability, and fitness for purpose of organisational data. Resilience: Investigates complex and recurring data quality issues, leading root cause analysis and follow-up actions to resolution while maintaining momentum across multiple stakeholders and open items. Future Focused: Supports the establishment of robust, sustainable data quality standards and controls that promote long-term data reliability and a culture of data quality across the organisation.