Senior Analytics Engineer

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About CMR Surgical

At CMR Surgical, we're revolutionising the future of minimal access surgery with Versius, our next-generation surgical robotic system. We're growing fast, and we're on a mission to transform how surgery is delivered globally-for the benefit of patients, clinicians, and healthcare systems.

Our values-Ambitious, Humble, People-Focused, and Fair & Responsible-define our approach to innovation, partnership, and growth. If you believe in making a meaningful difference in healthcare and want to be part of a purpose-driven company with bold ambitions, now is the time to join us.

CMR is an exciting and evolving company to be joining right now. Our commitment to our goal of building a world-class medical devices company is underpinned by the ground-breaking innovation of our next generation of surgical robots and a diverse team of talented and supportive individuals.

We're breaking new ground which makes working here exciting, it provides autonomy, opportunity and makes the things you do visible. Come and join us and see what you're capable of.

About the Role

We are looking for an Analytics Engineer to help build trusted, decision-grade data products across CMR Surgical. This role focuses on analytical data modelling, metric design, and repeatable analysis within our Databricks Lakehouse, with dashboards and reporting tools acting as downstream interfaces rather than the primary deliverable.

You will play a key role in moving us from ad hoc, tool-led reporting to a consistent, well-modelled analytics layer that stakeholders can rely on. The role combines analytical data modelling, SQL and Python-based analysis, and close collaboration with product owners and stakeholders

The role also involves performing exploratory and investigative analysis. This includes using SQL and Python notebooks to explore data, test hypotheses, and answer emerging business questions before those insights are operationalised into reusable metrics or data models.

This is a hybrid role with a minimum of 1 day per week in our Cambridge office.

Responsibilities

• Build and maintain trusted analytical data models (facts, dimensions, star schemas, semantic layers) within our Databricks Lakehouse
• Design, validate, and own core business metrics, to ensure consistency and correctness across business analytics
• Develop reusable analytical datasets and assets to support repeatable analysis and decision-making
• Perform ad-hoc exploratory analysis to answer business questions and support key decisions
• Translate exploratory analysis into scalable, reuseable analytics assets
• Support the transition from tool-led reporting to a scalable analytics layer by improving data models, metric definitions, and analytical workflows
• Maintain and progressively rationalise the existing Power BI estate while helping shift reporting onto well-modelled data products
• Partner with data engineering and product owners to translate business questions into scalable, reusable analytics assets

We'd expect you to be willing to turn your hand to anything within the data teams remit that helps the team deliver its objectives.

About You

To be successful in this role, you'll need to have/be:

• Pragmatic, delivery-focused mindset with a bias for clarity, simplicity, and maintainability
• Strong experience in analytical workflows, data modelling and metric design
  Proficient in SQL and Python
• Practical experience of exploratory analysis, data investigation and hypothesis testing
• Experience with modern analytics platforms such as Databricks, Snowflake, or similar Lakehouse/Warehouse environments
• Familiarity with BI and reporting tools with a clear understanding that dashboards sit on top of well-modelled data
• Experience working with stakeholders and product owners to define requirements and deliver decision-ready outputs
• Familiarity with the use of AI tools to help achieve the above aims

Interested? We'd love to hear from you!

This role requires candidates to have eligibility to work within the UK.

Strictly no agencies