Senior Data Platform Engineer (AWS, Databricks)

We are looking for a Senior Data Platform Engineer to take on the hardest parts of scaling our data platform which powers both internal and external analytics solutions, agentic AI workflows and wider engineering systems. We’re investing heavily in migrating workloads and services away from legacy infrastructure, as well as building repeatable and resilient data processing pipelines for these use cases.

Own the reliability and performance of our data lakehouse as it scales, taking the lead on the operational problems that don't have an obvious answer.

Build the infrastructure and business logic behind our data commercialisation products, partnering with product and commercial teams to turn data into revenue.

Design the abstractions, blueprints and reusable templates that let service and analytics teams work with data safely and consistently, from ingestion through to storage and access — and make them good enough that teams choose them.

Lead the data side of modernising our legacy monolithic SQL Server database: extracting into the lakehouse and parallel data stores, introducing retention policies, and migrating to modern SQL frameworks.

Write and optimise ETL processes and contribute to data modelling for both internal analytics and external-facing data products.

Take work from ambiguous problem statements through design, build and deployment, and stay accountable for it in production.

Raise the technical bar on how we build — reviewing designs, challenging decisions, and improving our engineering practices as you go.

Deep, hands-on experience building and running production data platforms and products

A good level of experience in Python (particularly pyspark) for building data pipelines