Senior Data and Insights Lead

Ravensbourne University London is a dynamic institution at the intersection of creativity, business, and technology. Based in London's Design District in the heart of North Greenwich, we are home to a diverse, global community in one of the world's most vibrant business and creative hubs.

We are looking for a Senior Data and Insights Lead to join our Planning and Insights team and help transform how the University uses data to plan, prioritise and make decisions.

This is a senior, hands-on role which combines leadership of development of our data modelling capability, translation of data into useful institutional insight, and hands-on delivery of data solutions. You will lead the development of trusted, reusable data models and reporting products, with a particular focus on the student lifecycle, while supporting insight needs across the whole University.

Success will require balancing two different modes of delivery. You will be establishing proportionate standards and driving implementation of enterprise data modelling, while also enabling rapid, pragmatic analysis and short-life solutions when decisions cannot wait. You will know when to build for scale, when to prototype, and how to prevent useful tactical work from becoming unmanaged technical debt.

What you will do:

Lead the development and ongoing management of the University's insights environment, creating coherent and trusted data models that support a single, well-governed view of performance.

Translate strategic and operational questions into timely reports, dashboards, forecasts and actionable insight for the Executive and wider leadership community.

Design scalable semantic and analytical models, principally using SQL and Power BI, with clear definitions, ownership, documentation, testing and change control.

Deliver rapid prototypes and focused quick-and-dirty builds where there is a clear business need, applying sensible controls, making limitations explicit and agreeing whether solutions should be retired, improved or incorporated into the enterprise model.

Lead planned and ad hoc analysis, applying statistical and forecasting techniques to identify trends, risks and opportunities.

Create intuitive self-service reporting that helps colleagues answer routine questions independently and support the adoption of meaningful use of institutional data.

Work in partnership with IT Services and data owners to improve architecture, integration, data quality and governance, and to ensure reporting requirements can be supported sustainably.

Build analytical capability across the University through clear communication, practical guidance and targeted training for technical and non-technical audiences.

Lead and develop data and insights colleagues, setting priorities, allocating work and creating an environment in which quality, curiosity, pace and continuous improvement are expected and recognised.

Maintain a strong understanding of the UK higher education policy, regulatory and market context, ensuring that data models and analysis reflect the realities of institutional decision-making.

You will bring:

Extensive relevant experience at a senior level in data analysis, business intelligence, institutional planning or a closely related field.

A strong track record of developing data models, dashboards and analysis that have influenced organisational decisions.

Advanced capability in SQL and Power BI, or demonstrably transferable expertise in comparable tools (e.g. Python, R, Tableau).

Practical understanding of dimensional modelling, semantic models, data quality, metadata, testing, documentation and controlled deployment.

The ability to scope and prioritise competing demands, retain flexibility when unexpected needs arise, and explain the trade-offs between speed, quality and sustainability.

Experience of presenting evidence and recommendations to senior stakeholders, including audiences with differing levels of data literacy.

A good understanding of higher education data and processes across the student lifecycle, alongside an awareness of wider institutional domains such as finance, people, estates, research and enterprise.

Experience of working with student information systems; experience of SITS would be particularly valuable.

The ability to coach and develop colleagues, promote good analytical practice and build confidence in the use of data.

Experience of predictive modelling, advanced statistical analysis and line management would be advantageous.

We offer:

Generous leave. Hybrid working model of on-site and working from home. Competitive Pension Scheme. An Employee Assistance programme. A cycle-to-work scheme.