Analytics Engineer

The Role: At Canopius, our delivery teams are responsible for ensuring that business users can effectively harness data insights to drive strategic decision making. Our data strategy is centred around an enterprise Lakehouse platform on Databricks, avoiding fragmented, ungoverned silos on legacy technologies that hamper creativity and scalability. We are building a governed, interoperable data estate that enables self-service for our business teams and provides the trusted foundation for advanced analytics, machine learning and AI to accelerate change across our industry. This role is an opportunity to apply and develop your expertise in analytics engineering, data modelling and visualisation to build, extend and maintain the analytics and reporting capabilities that are central to decision making across Canopius. You will contribute to business transformation projects, working closely with colleagues across Data and with business stakeholders, and using modern technologies such as Power BI and Databricks to deliver trusted, accessible insight. The ideal candidate is an analytics engineer looking for a new challenge who is enthusiastic about using technology to improve how insight is delivered and consumed. You should be able to understand business problems, translate them into clear requirements and deliver reliable solutions tailored to our needs, while applying good analytics engineering practices and seeking guidance where appropriate. You should be comfortable collaborating and working as part of a dynamic multi-disciplinary team. This role supports delivery of Canopius’ data strategy by helping to turn a governed, interoperable data estate into trusted, self-service insight. Alongside hands-on development, the role will contribute to the transition of legacy reporting onto modern platforms and help ensure that analytics solutions are well designed, documented, supportable and aligned to agreed team standards. Hybrid Working We operate a hybrid working policy, combining the flexibility of home working with regular time together in the office. For this role, you will be expected to work 2–3 days per week from our Manchester city centre office. Responsibilities will include: Develop analytics engineering and reporting solutions that help business users access trusted insight and make informed decisions. Work with business stakeholders, Product Owners, Business Analysts and other Data colleagues to understand information needs and translate them into clear, deliverable requirements. Design, build and maintain semantic models, datasets and reporting solutions using Power BI, paginated reports and Databricks, applying agreed team standards and development practices. Support report and dataset performance improvement by reviewing data models, DAX calculations, queries and refresh approaches, escalating more complex optimisation needs where required. Apply data validation, reconciliation and testing approaches to ensure analytics outputs are accurate, reliable and aligned to approved sources. Document solutions clearly, including data sources, logic, refresh schedules, access requirements and support considerations. Follow team standards for modelling conventions, naming, testing, deployment and version control, contributing suggestions for improvement where appropriate. Support the rationalisation and redevelopment of legacy reporting solutions as part of their migration onto modern platforms. Communicate analytics outputs, assumptions, risks and limitations clearly to both technical and non-technical audiences. Plan and manage assigned work items, producing realistic estimates, highlighting dependencies and raising risks or blockers early. Participate in peer review, knowledge sharing and team ceremonies, giving and receiving constructive feedback to improve solution quality. Use modern analytics engineering practices, automation opportunities and AI-assisted tools where appropriate to improve delivery quality and efficiency. Keep abreast of developments and trends in data, analytics and reporting technology. Manage own task list and ensure that plans and priorities are agreed. Undertake other ad-hoc duties as required. Skills and Experience Hands-on development experience with Power BI, including DAX, tabular/semantic models and paginated reports. Good understanding of analytics engineering principles, semantic/dimensional modelling and cloud-based data platforms. Experience building clear, reliable and user-friendly reports and dashboards that support business decision making. Good SQL skills for querying, analysing and transforming data. Familiarity with Azure DevOps, Git and development lifecycle practices, including peer review, testing and deployment processes. Experience working in an Agile or Scrum environment and contributing effectively within cross-functional teams. Analytical and problem-solving skills with good attention to detail and a continuous improvement mindset. Good communication skills, with the ability to explain analysis, assumptions and solution choices clearly to technical and non-technical audiences. Experience with AI-assisted development tools and copilots to improve productivity and delivery outcomes is advantageous. Familiarity with Tabular Editor and Databricks is desirable. Familiarity with specialty (re)insurance or Lloyd’s market data such as bordereaux, delegated authority, underwriting and claims is advantageous.