Analytics Engineering Manager

The role:

Analytics Engineering provides the trusted enterprise foundation for insight. It creates reusable products, patterns and standards that business-aligned analytics teams can adopt and extend, while enabling business users to self-serve with confidence. By defining business logic and measures once for common use, the team accelerates delivery, reduces duplication and manual effort, and ensures reporting and insight remain consistent, governed and reusable.

As Analytics Engineering Manager, you will lead the capability end to end, setting technical direction, developing the team and partnering with business leaders to turn priority needs into scalable analytical solutions and governed self-service capabilities. You will remain sufficiently close to the technology to challenge major design decisions and uphold engineering quality, while leading delivery through senior engineers and driving organisation-wide adoption of shared analytical products and standards.

This is an opportunity to lead the next evolution of Analytics Engineering at Canopius, expanding from shared capabilities and common standards to a federated model that builds analytics expertise within business teams, broadens access to trusted insight and enables faster self-service. The ideal candidate will combine strong analytics engineering expertise with the ability to build confidence, drive adoption, develop teams and influence senior business and technology stakeholders.

This is a hybrid role, working 2-3 days per week from our Manchester office

Responsibilities will include:

• Set the strategic and technical direction for Analytics Engineering, creating reusable analytical solutions, patterns and standards that provide a trusted foundation for insight across the organisation.
• Establish and maintain the single version of business logic and analytical standards, ensuring business teams work from consistent definitions, calculations and measures.
• Broaden access to trusted insight, enabling business users to answer their own questions through analytical capabilities, clear guidance, structured training and ongoing support.
• Enable business-aligned analytics teams to adopt and extend shared analytical products and standards within a federated model, with appropriate controls over sensitive data.
• Work with business leaders to translate priority questions into shared analytical products, agree baselines with accountable business owners, and track adoption, reuse, time to insight and realised business value.
• Partner with business teams to identify and automate repetitive, manual reporting and analytical processes, reducing effort, spreadsheet dependency and operational risk.
• Embed modern, AI-assisted practices across development and delivery processes to improve productivity, quality and consistency, enabling the team to scale its impact.
• Lead the end-to-end delivery of complex analytics initiatives, managing dependencies, risks, technical debt, and stakeholder expectations.
• Partner with Change, IT, Architecture, Product and business teams to ensure coherent solution design, effective prioritisation and joined-up delivery.
• Lead, line manage and develop the Analytics Engineering team across internal and strategic partner resources, setting measurable objectives, managing performance, supporting career growth, building succession strength and fostering an inclusive, accountable culture of continuous improvement.
• Oversee production service delivery for analytical products and services, ensuring availability, reliability, performance, issue resolution, release management and change control meet business needs and organisational resilience requirements.
• Communicate technical solutions, trade-offs, risks, opportunities and delivery performance to technical, business and executive audiences, influencing decisions with evidence-based recommendations.
• Undertake other ad-hoc duties as required.

Further Relevant Skills and Experience

• Demonstrable experience leading analytics engineering teams, developing talent and building an inclusive, accountable and high-performing culture.
• Proven ability to translate business priorities into scalable analytical products and self-service capabilities that improve decision-making and deliver measurable value.
• Extensive analytics engineering experience, with strong knowledge of reusable data-product design, analytical patterns and the implementation of consistent business definitions, calculations and performance measures.
• Practical experience in Databricks and Power BI, including data transformation, orchestration, semantic model design, performance optimisation and deployment.
• Demonstrable experience driving adoption of analytical products, engaging users throughout delivery, and establishing baseline metrics and business value tracking in collaboration with business owners.
• Experience establishing and embedding frameworks to enable business-aligned analytics teams to extend shared products, following common standards and best practices.
• Proven delivery of secure, governed and reliable enterprise analytics solutions using source control, automated testing and controlled release practices.
• Strong business partnering and communication skills, with the ability to challenge priorities, explain complex topics clearly and influence technical, business and executive stakeholders.
• Experience leading complex, cross-functional analytics initiatives, balancing technical quality, governance, user needs, delivery speed and business value while managing dependencies and stakeholder expectations.
• Experience owning production analytics services, including reliability, incident, change and release management, and organisational resilience controls.
• Ability to apply AI-assisted development tools where they improve engineering productivity, quality and delivery outcomes.
• Experience of working with specialty insurance data is advantageous.