About the role

Senior Analytics Platform Engineer designing and maintaining data models at Our Future Health. Collaborating across teams to enable reliable data analytics for better health outcomes.

Responsibilities

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.

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.

Generous Pension Scheme – We invest in your future with employer contributions of up to 12%.
30 Days Holiday + Bank Holidays – Enjoy a generous holiday allowance with the flexibility to take bank holidays when it suits you.
Enhanced Parental Leave – Supporting you during life’s biggest moments.
Cycle to Work Scheme – Save 25-39% on a new bike and accessories through salary sacrifice.
Home & Tech Savings – Get up to 8% off on IKEA and Currys products, spreading the cost over 12 months through salary sacrifice
£1,000 Employee Referral Bonus – Know someone amazing? Get rewarded for bringing them on board!
Wellbeing Support – Access to Mental Health First Aiders, plus 24/7 online GP services and an Employee Assistance Programme for you and your family.
A Great Place to Work – We have a lovely Central London office in Holborn, and offer flexible and remote working arrangements.