As a Staff Analytics Platform Engineer, you’ll provide technical leadership across the entire analytics platform, from ingestion and transformation tooling to Snowflake architecture, semantic modelling, and secure analytics environments. You’ll define the patterns, standards, and infrastructure that enable analysts, data scientists, and product teams to build reliable, scalable analytics with confidence. This is a role where your decisions shape the platform for years to come, and your impact multiplies across every team that uses data.

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

• Co‑owning the analytics platform architecture, designing end‑to‑end solutions across Snowflake, ingestion pipelines, dbt infrastructure, semantic layers, and secure analytics environments.
• Defining and driving the long‑term technical vision for the analytics platform, ensuring it is scalable, cost‑efficient, secure, and easy for data consumers to use.
• Establishing architectural principles and patterns that balance reliability, governance, usability, and performance across the entire data ecosystem.
• Leading high‑impact platform initiatives that improve performance, developer experience, cost efficiency, or operational maturity.
• Owning and evolving core platform components, including CI/CD, testing strategies, environment management, observability, and infrastructure as code.
• Acting as the technical escalation point for complex, cross‑cutting platform issues and guiding teams toward robust, scalable solutions.
• Driving Snowflake performance and cost optimisation, informed by real workloads and modelling patterns.
• Implementing and maturing data SLAs/SLOs, data observability, lineage, and quality frameworks to ensure trusted analytics at scale.
• Collaborating with data product and engineering teams to enable safe, scalable ingestion and well‑defined data contracts.
• Influencing how teams design and interact with data systems, raising engineering standards across the organisation.
• Providing technical mentorship to analytics engineers and platform engineers, helping elevate capability across the data function.

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.

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

• Deep experience building and running modern data platforms in complex, multi‑team environments.
• Excellent Python engineering skills and the ability to design scalable, reliable platform components.
• Expertise in analytics data modelling and how modelling choices affect performance, cost, and usability.
• Hands‑on experience with ingestion/orchestration tooling (such as Airbyte) and scaling pipelines across many sources.
• Proven technical leadership across infrastructure, ingestion, transformation, and analytics enablement.
• Strong platform architecture experience: Snowflake, dbt execution, semantic layers, secure analytics environments.
• Ability to diagnose complex, cross‑cutting issues across data, infrastructure, and analytical workloads.
• A track record of improving developer experience and reducing friction in data development.
• Clear, influential communication skills with the ability to align teams around platform strategy.
• Experience mentoring engineers and raising capability across data and platform teams.
• Hands‑on dbt and analytics CI/CD experience.
• Experience with Kubernetes and cloud‑native environments.
• Familiarity with semantic layers and BI tooling (such as Omni).
• Experience supporting secure notebook environments (Coder, Jupyter, RStudio).
• Comfort working in regulated environments with strong governance and audit needs.
• Knowledge of Terraform, data governance models, and data observability tooling.

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.