Own Fetch’s data platform end-to-end – from ingestion and modelling to observability, experimentation, and AI evaluation
Design the data foundations that make AI safe, measurable, and reliable: datasets, evals, feedback loops, and monitoring that keep our agents honest
Build and own Fetch’s entire data stack – ingestion, pipelines, warehouse, observability
Partner with AI engineers to productionise agents and models with clear metrics, feedback loops, and evaluation frameworks
Make data flow in real-time across pricing, product, claims, ops, and AI
Automate everything – alerts, tests, and fail-safes so nothing breaks silently
Enable smarter pricing, sharper decisions, and clearer insight across the business
Partner with engineering and AI teams to productionise data-driven features

5+ years building and maintaining data platforms or analytics engineering stacks at scale
Strong with Python and SQL, and comfortable with dbt, modern warehouses, and event-driven data
Experience designing reliable batch and/or streaming pipelines with strong observability and testing
Pragmatic builder – you know when to ship a simple solution and when to invest in scalable architecture
You care about product: you like to understand the business problem, challenge requirements, and push for outcomes over output
Obsessed with data quality, trustworthiness, and clear definitions (metrics, contracts, schemas)
Clear communicator, effective collaborator across engineering, product, ops, and leadership
Bonus – experience designing evaluation frameworks for AI/LLM systems (offline evals, golden sets, regression tests, monitoring)
Bonus – experience supporting AI agents or ML products (feature engineering, feedback loops, human-in-the-loop systems)
Bonus – experience in insurance, healthcare/veterinary, fintech, or other regulated environments

Data Engineering Lead – AI, Analytics, Platform

Key skills