As a Senior Analytics Platform Engineer, you’ll design and maintain analytics‑ready data products that enable consistent, reliable insight at scale. You’ll work across the analytics platform, data product teams, and scientific users to improve how data is modelled, documented, and adopted, while also coaching others to build high‑quality analytical assets with confidence. This is a role where your impact multiplies, success means everyone can build better analytics, not just you.

At Our Future Health, our mission is to transform the prevention, detection and treatment of conditions such as dementia, cancer, diabetes, heart disease and stroke.  We’re looking for people to join us on our journey. If you’re looking for a new challenge where you can contribute to helping future generations live in good health for longer, then we’re keen to speak with you.

What you’ll be doing

• Designing and maintaining analytics‑ready data models in Snowflake using dbt, including data marts, metrics, and reusable analytical datasets.
• Applying scalable modelling patterns and contributing to organisation‑wide standards and conventions.
• Coaching analysts, data scientists, and science teams in analytics engineering best practice, modelling, testing, documentation, and data quality.
• Enabling domain teams to own and maintain their data marts safely and confidently, with guidance and review to ensure alignment with platform standards.
• Partnering with internal researchers to translate exploratory analysis into repeatable, well‑modelled datasets with clear definitions and reproducible insights.
• Shaping analytical products around real use cases, ensuring data marts are intuitive, discoverable, and fit for purpose.
• Owning data quality at the analytics layer, using dbt tests, monitoring, and close collaboration with platform engineers to resolve issues.
• Building and maintaining the semantic layer in Snowflake and Omni to support consistent, self‑serve analytics.
• Supporting adoption of Omni through documentation, examples, and hands‑on guidance.
• Collaborating with data product teams on ingestion, data contracts, and quality expectations.
• Working closely with Analytics Platform Engineers on dbt execution patterns, performance optimisation, and CI/CD improvements.
• Mentoring mid‑level analytics engineers and contributing to a culture of high‑quality, scalable analytics.

What you won’t be doing

• Working in a siloed environment with no freedom to make decisions.
• Working in a place where you can’t see the impact your expertise makes.

At Our Future Health, we recognise the importance of having a diverse workforce and ensuring that all candidates, regardless of their background, have equitable access to our application process. We proactively encourage applicants who identify as having a disability, neurodiversity, or long-term health conditions to let us know if they require any reasonable adjustments as part of their application process. 

If you do require any reasonable adjustments, please email us at talent@ourfuturehealth.org.uk 

To succeed in this role you will be able to demonstrate some of the following skills and experience:

• Proven analytics engineering experience with a track record of building analytics‑ready datasets.
• Python engineering ability to produce clean, maintainable, production‑grade code.
• Hands‑on dbt expertise including modelling, testing, documentation, and data quality.
• Understanding of metrics and KPIs and how to translate them into well‑structured data models.
• Experience working with analysts and data scientists to support and enable analytical work.
• Clear, empathetic communication to explain modelling decisions to non‑engineers.
• A coaching mindset that helps domain teams take ownership of their models.
• Strong analytical problem‑solving with a focus on clarity, simplicity, and maintainability.
• Comfort navigating complex data ecosystems and shaping standards across teams.
• Interest in platform‑level concerns such as performance, orchestration, CI/CD, and reliability.
• Experience with cloud‑native tooling including Kubernetes and containers.
• Familiarity with semantic layers such as Snowflake, Omni, or Looker.
• Experience in regulated or scientific environments where governance and reproducibility matter.

Disclaimer: We will be interviewing for this role as suitable applications are received and may close this role before the closing date upon a successful candidate being appointed.