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.
