Senior Analytics Engineer (AI)

TL;DR

Senior Analytics Engineer (AI): Modelling raw data into production-ready tables for stakeholders and AI products that underpin business decisions with an accent on scalable data models, AI/LLM readiness, and governance. Focus on architecting core data pipelines, supporting feature engineering for AI workflows, and ensuring data integrity for high-impact analytics and patient-facing tools.

Hybrid in London

Company

Fast-growing healthcare scale-up building AI-powered products for patient interactions.

What you will do

• Architect, model and optimise core data models for analytics and AI applications, building for scale and performance.
• Structure data layer to support AI/LLM use cases including feature pipelines, evaluation datasets and clean documentation.
• Partner with marketing, finance, operations and product teams to translate requirements into reliable technical solutions.
• Own data governance, integrity, consistency, security, documentation and best practices for owned models.
• Shape data culture by driving adoption of modeling frameworks and analytical standards.
• Identify and implement improvements to data stack performance, reliability and usability.

Requirements

• Working understanding of AI/LLM data consumption, feature engineering, evaluation pipelines and data quality standards.
• Experience supporting AI/ML workflows like feature stores or training data curation.
• 3+ years in analytics engineering, data engineering or similar.
• Advanced SQL for designing, optimising and debugging complex queries.
• Hands-on with dbt or Dataform for scalable data models; BigQuery and Looker advantageous.
• Strong data analysis, statistics, governance, quality assurance and documentation skills.

Culture & Benefits

• High-impact role in fast-paced scale-up influencing company-wide operations and AI product performance.
• Genuine ownership over data models and governance practices.
• Work closely with data and business stakeholders as bridge between raw data and insights.
• Modern data stack: BigQuery, dbt, Looker.
• Opportunity to shape scalable standards for growth across products and markets.