Senior Analytics Engineer

Our Future Health is an ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation of new diagnostic tools, to help identify and treat diseases early, when outcomes are usually better. With over 2.5M volunteers across the UK, we’re now the world’s biggest health research programme of its kind, and our volunteer group is also more diverse than other, similar health research programmes. 

Technology and data are central to our mission. Our systems power web sites, clinics across the UK, secure analytics and research systems, pipelines that process highly sensitive health and genetic data, and we are continuing to grow our engineering capability to support this ambition. 

We’re now growing our analytics engineering capability, recognising it as critical to unlocking the value of our data. This is a chance to join early, shape the function, and work on genuinely unique health data challenges

The Senior Analytics Engineer plays a strategic and technical leadership role in enabling high quality, consistent, and scalable analytics across the organisation. This role not only delivers trusted data models but also sets standards, drives best practices, and shapes the direction of analytics engineering. 

By leading on modelling approaches, mentoring analysts and data scientists, and partnering with stakeholders across the organisation, the role amplifies impact at scale, ensuring analytics is robust, reusable, and aligned to strategic priorities. This role is critical in advancing the organisation’s analytics maturity and building a future-ready data platform. 

Why join? 

• Work with large-scale, real-world health data  
• Build trusted, reusable data products used across science and business  
• Help develop data quality, testing, and observability from the ground up  
• Enable self-serve and AI-powered analytics for non-technical users  
• Join at an early stage of team growth with real influence, you’ll lead initiatives and work directly with stakeholders 
• Mission-led: your work contributes to improving health outcomes at scale  

You will: 

Lead development of high-quality analytics data models 

• Architect and build scalable, well-governed dbt models in Snowflake, including data marts, metrics, and reusable datasets.  
• Define and evolve modelling standards, conventions, and best practices across the organisation.  
• Review and guide implementation of models to ensure consistency, scalability, and performance.   

Set standards and enable teams 

• Act as a technical leader and mentor for analytics engineers, analysts, and data scientists.  
• Establish best practices for modelling, testing, documentation, and data quality.  
• Enable domain teams to safely own and extend their data models within a governed framework.  

Strategic partnership with business and science teams  

• Translate complex analytical and research problems into scalable, production-grade data models.  
• Shape how metrics and datasets are defined and used across the organisation.  
• Influence stakeholders on best practices in data usage, reproducibility, and analytical design.   
• Improve data quality, documentation, and reproducibility in workflows  

Own data quality and reliability frameworks 

• Design and implement robust testing, monitoring, and alerting frameworks for analytics data.  
• Define SLAs and data quality standards in collaboration with platform and data engineering teams.  
• Lead root-cause analysis and resolution of data quality issues.  

Drive self-serve analytics at scale  

• Own and evolve semantic layers in Snowflake and BI tools (e.g., Omni).  
• Define governed approaches to metrics and self-serve analytics.  
• Champion adoption through clear documentation, training, and enablement strategies.  

Contribute to and shape the Analytics Platform  

• Partner with platform engineers on architecture, performance optimisation, and orchestration.  
• Drive improvements in analytics CI/CD, deployment workflows, and developer experience.  
• Influence data contracts, ingestion patterns, and overall platform design. 

We’re London-based (Holborn) and work on a flexible hybrid basis (typically weekly with a team day every 2 weeks). We'd like to prioritise candidates who can reasonably commute and benefit from in-person collaboration.