Data & Analytics Manager (Development)

Function / Area: IT & Operations / Data & Analytics team

Reporting to: AVP, Data Analytics

Position Summary

As a Data and Analytics Manager (Development) you will lead the development and execution of data solutions. This role blends leadership, technical execution, and business alignment – delivering value across the enterprise through data-driven transformation.

Key Responsibilities

• Oversee the development and execution of enterprise-wide data analytics strategies that align with business objectives, driving innovation and efficiency.
• Lead the design and deployment of sophisticated analytical models and dashboards to uncover insights, predict trends and inform decision-making across the organisation.
• Work closely and in collaboration with Underwriting, Claims, Actuarial, and IT teams to integrate analytics into core business functions, enhancing overall performance.
• Collaborate and provide strategic data support to enterprise-wide transformation initiatives, ensuring alignment with business objectives and digital innovation goals.
• Lead and coach a hybrid team of data and analytics specialists and data engineers distributed across onshore and offshore locations.
• Responsible for work estimation and resource allocation aligned with prioritisation from the Business Insights group to support timely and effective project delivery.
• Manage JIRA project tracking, maintain confluence documentation and oversee code design to support efficient development processes and team collaboration.
• Oversee technical designs for data models, ETL and visualization tools (like SSIS, Tableau, SSRS).
• Support global reporting initiatives driven through the US data and analytics programs, ensuring consistency, compliance, and alignment with international business priorities.
• Ensure that all the analytical code and data pipelines adhere to best practices for readability, maintainability and efficiency using clean code principles and modular design.
• Oversee the design and implementation of data pipelines, APIs and model deployment infrastructure in collaboration with DevOps teams to ensure reliable and efficient deployments.
• Define and implement best practices in data modeling e.g. Warehousing and Lakehouse integration (Medallion Architecture).
• Collaborate and lead efforts in defining, designing, and standardizing data development and metadata management practices to ensure consistency and quality in technical architecture.
• Oversee metadata management, lineage tracking and orchestration tools.
• Ensures quality of reporting solutions by performing code review, creating documentation, and completing unit and integration testing.
• Own technical resolutions following incidents and lead the root cause analysis to ensure long term issue remediation.
• Establish and enforce best practices for change control, rollback strategies, and testing to ensure stable production deployments.
• Ensures customer satisfaction through meeting established development and service level standards.
• Ensure audit readiness through documentation, lineage, and access control protocols to comply with all applicable legal and regulatory requirements appropriate to the position.
• Manage relationships with external vendors and technology partners delivering analytics services and solutions.
• May perform additional duties as assigned.

Skills, Knowledge & Abilities

Essential

• Deep understanding of structured data management and enterprise best practices.
• Proven track record in implementing Business Intelligence (BI) solutions and supporting operational dashboards to drive data-informed decision-making.
• Experience with both normalized, star and multidimensional schema design.
• Understanding of ETL processes and data warehousing concepts, including handling slowly changing dimensions.
• Excellent interpersonal and communication skills, enabling effective collaboration with business stakeholders, technical teams, consultants, and vendor partners.
• Proven ability to articulate analytical and technical concepts to non-technical audiences, fostering stakeholder buy-in.
• Strong analytical and problem-solving skills with attention to detail.
• Skilled in managing multiple priorities, with the ability to effectively prioritize tasks.
• Excellent knowledge of Microsoft Business Intelligence (SSIS, SSRS).
• Proficient in SQL Server with hands-on experience in SQL data querying and optimization Control-M scheduling.
• Google Platform Composer, BigQuery and VertexAI.
• Tableau experience.
• Python programming.

Desirable

• Insurance background with knowledge of industry reporting and KPI’s / KRI’s.
• Knowledge and experience of finance and insurance data models.
• Alteryx.

CNA Hardy is an equal opportunity employer.