You will join our Data team as a senior analytics engineer modelling raw data and turning it into production ready tables for stakeholders and AI products that underpin the decisions that shape our business. This is a high-impact role at the heart of a fast-growing healthcare scale-up — one where the data you model and the standards you set will directly influence how every team in the company operates, and how well our AI-powered products perform.

You'll work closely with data and business stakeholders. You will be the bridge between raw data and meaningful insight, ensuring our modern data stack — built on BigQuery, dbt and Looker — is scalable, trusted and AI-ready. Your work will underpin both the analytical decisions of our internal teams and the performance of the patient-facing AI tools we build.

You'll have genuine ownership over the data models and governance practices that underpin our data function. At a company growing as fast as ours, the standards you establish today will shape how we scale tomorrow — across products, markets and millions of patient interactions.

What you'll do

• Architect, model and optimise the core data models that power analytics and AI applications across the business, building for scale and performance from the ground up.

• Ensure the data layer is structured to support AI and LLM use cases — including feature pipelines, evaluation datasets and the clean, well-documented data that reliable AI products depend on.

• Partner with cross-functional teams across marketing, finance, operations and product to translate business requirements into robust, reliable technical solutions.

• Own data governance of the data models you own — ensuring integrity, consistency and security while maintaining documentation and enforcing best practices.

• Shape our data culture, driving adoption of rigorous modeling frameworks and analytical standards.

• Identify opportunities to improve the performance, reliability and usability of our data stack, and take full ownership of seeing those improvements through.

Who you are

AI & LLM awareness priority

• A working understanding of how AI and LLM-powered products consume data — including familiarity with feature engineering, evaluation pipelines and the data quality standards these systems require.

• Experience contributing to or supporting AI/ML workflows, whether through building feature stores, curating training data, or structuring outputs for model consumption.

Technical expertise

• 3+ years of experience in analytics engineering, data engineering or a closely related role.

• Advanced SQL skills — you can design, optimise and debug complex queries with confidence.

• Hands-on experience with dbt or Dataform, and a strong track record of building scalable, well-structured data models.

• Comfortable working within a modern data stack; direct experience with BigQuery and Looker is a strong advantage.

Analytical acumen

• Strong understanding of measurement approaches, data analysis and statistics — you think carefully about what a metric actually means before you build it.

• Able to hold both the technical and business context simultaneously, ensuring every data solution is anchored to a real company objective.

• Experienced in data governance, quality assurance and documentation — you understand that trusted data is the product.

How you work

• A natural collaborator who can earn the trust of both data analysts and non-technical stakeholders alike.

• Takes ownership end-to-end — from understanding a business problem to delivering a solution the whole company can rely on.

• Excited by the challenge of building in a fast-paced environment and motivated by the idea that your work helps improve patient outcomes at scale.

• Someone who resonates with ownership, strategic thinking and the pace of a high-growth scale-up.