Data & Analytics Manager in London

The Company is a well-established and specialist commercial insurer operating across domestic and international markets. The organisation offers a comprehensive portfolio of innovative risk solutions and services to businesses of all sizes, with a strong emphasis on data-driven decision-making and digital transformation.

The Role will lead the development and delivery of enterprise-wide data solutions. The role combines technical leadership, stakeholder engagement, and hands-on execution to support business growth and operational excellence through advanced analytics and data strategy.

Key Responsibilities

• Develop and lead the execution of data and analytics strategies aligned to wider business objectives.
• Design and deploy advanced analytical models and dashboards to extract insights, forecast trends, and inform strategic decision-making.
• Collaborate with functions including Underwriting, Claims, Actuarial, and IT to integrate data solutions into day-to-day operations.
• Provide data expertise and support to transformation initiatives, ensuring alignment with digital innovation programmes.
• Manage and mentor a hybrid team of data analysts, engineers, and specialists across both onshore and offshore locations.
• Coordinate task prioritisation, resource allocation, and delivery timelines in collaboration with the Business Insights team.
• Oversee project tracking using JIRA, ensure up-to-date documentation in Confluence, and guide robust code and solution design.
• Lead the design and maintenance of data models, ETL processes, and visualisation tools (e.g. SSIS, Tableau, SSRS).
• Support and align with global reporting programmes to ensure consistency and compliance with international standards.
• Maintain high standards of code quality, readability, and maintainability, following clean code principles and modular architecture.
• Oversee the development and deployment of data pipelines, APIs, and machine learning models in coordination with DevOps teams.
• Define and embed best practices for data warehousing and Lakehouse architecture (e.g. Medallion).
• Standardise data development, modelling, and metadata management across the enterprise.
• Implement lineage tracking and orchestration tools to improve transparency and governance.
• Conduct code reviews, testing, and documentation to ensure quality and robustness of analytics outputs.
• Take ownership of incident resolution and lead root cause analysis to ensure sustainable remediation.
• Enforce best practices for change control, release management, rollback planning, and deployment testing.
• Maintain high levels of internal client satisfaction by ensuring deliverables meet service level expectations.
• Ensure audit readiness through documentation, access control, and data lineage practices in line with regulatory standards.
• Manage third-party vendors and technology partners providing analytics tools or support services.
• Undertake additional responsibilities as required to support the broader data strategy.

Skills, Knowledge & Abilities

Essential:

• Strong understanding of enterprise data management and governance principles.
• Proven experience delivering Business Intelligence (BI) solutions and dashboards to enable data-driven decisions.
• Experience designing relational and dimensional data models (e.g. star schema, snowflake, etc.).
• Proficient in ETL and data warehousing, including handling slowly changing dimensions.
• Excellent communication and interpersonal skills, with the ability to liaise confidently between technical and non-technical stakeholders.
• Demonstrated ability to influence and engage across business functions and with external partners.
• Strong analytical thinking and a methodical approach to problem-solving.
• Skilled at managing multiple workstreams and priorities effectively.

Technical Expertise:

• Advanced knowledge of Microsoft BI tools (SSIS, SSRS).
• Strong SQL Server skills, including query optimisation and performance tuning.
• Familiarity with scheduling and orchestration tools (e.g. Control-M).
• Hands-on experience with Google Cloud tools such as BigQuery, Composer, and VertexAI.
• Proficient in Python for data manipulation and modelling.
• Strong skills in data visualisation using Tableau.

Desirable:

• Background in insurance or financial services, with exposure to industry-specific metrics (KPIs/KRIs).
• Familiarity with insurance data models and reporting frameworks.
• Experience using Alteryx for data preparation and workflow automation.