Data Analytics Engineer

escription

Data Solutions team is at the heart of the business, building the data
products and analytical capabilities that underpin our Decision Engine platform, power vehicle
intelligence, and drive performance insight across the organisation.

As Analytics Engineer, you will sit at the intersection of data engineering, data science, and product
delivery. You will be the dedicated technical resource for the Decision Engine Product Manager,
Vehicle Data Lead, and Lead Data Scientist, enabling faster, more rigorous analysis, cleaner data
pipelines, and more reliable analytical outputs across all three workstreams.
This is a high-impact, high-visibility role for someone who is technically strong, commercially
curious, and energised by working across diverse product and science problems in a fast-moving
environment.

Data Solutions is a team of approximately 15 across Decision Engine product, Data Science,
Operational Reporting, and Vehicle Data & Platform. We operate in a hybrid model and value
autonomy, rigour, and genuine curiosity about the commercial problems we are solving.

You will work closely with senior colleagues across product and science, and have direct visibility
into some of the most strategically significant data capabilities in Cox Automotive Europe. This is a
role for someone who wants to do meaningful technical work and see it matter.

Requirements

Essential
• Strong SQL and Python skills, with practical experience building and maintaining data
transformation pipelines
• Hands-on experience with a modern data stack (Databricks, dbt, or equivalent)
• Ability to translate ambiguous analytical requirements from product managers, data
scientists, and business stakeholders into reliable, well-documented pipelines
• Experience working in a commercial or product-focused data environment
• Strong understanding of data modelling principles — from raw ingestion through to analytical
layer design
• Comfortable working across multiple concurrent workstreams with competing priorities
• Clear, confident communicator — able to explain technical approaches to non-technical stakeholders
Desirable
• Experience with automotive, marketplace, or pricing/valuation data
• Familiarity with ML feature engineering and supporting data scientists in production
environments
• Exposure to Rally, Jira, or similar agile delivery tooling
• Knowledge of data governance, lineage, and cataloguing practices
• Experience with A/B testing frameworks or experimentation analytics