Analytics Engineer

Job Title Analytics Engineer Job Description Summary Analytics Engineer | Databricks | Agentic AI | EMEA & APAC We lead the data transformation of our EMEA and APAC business, and we are looking for an Analytics Engineer to join us. Our lakehouse platform is mature and well established. It is built on Databricks and already runs the business end to end. What comes next is the harder part, putting agentic capability to work at real enterprise scale and across a wide range of domains. You will take on problems nobody has written the playbook for, make calls that matter, and build depth across several domains early enough to shape where the platform goes next. Very few organisations in our sector have started this work, so you will pick up a skill set you would struggle to find anywhere else in this industry. You will sit between data engineering and the business. That means turning commercial questions into semantic models, curated datasets and reusable data assets that leaders across EMEA and APAC rely on, working with our engineers on the upstream design that keeps those assets scaling, and getting them ready for agentic and AI-led delivery. If you want work that carries real weight, we would like to hear from you.

We lead the data transformation of our EMEA and APAC business, and we are looking for an Analytics Engineer to join us.   Our lakehouse platform is mature and well established. It is built on Databricks and already runs the business end to end. What comes next is the harder part, putting agentic capability to work at real enterprise scale and across a wide range of domains.   You will take on problems nobody has written the playbook for, make calls that matter , and build depth across several domains early enough to shape where the platform goes next. Very few organisations in our sector have started this work, so you will pick up a skill set you would struggle to find anywhere else in this industry.   You will sit between data engineering and the business. That means turning commercial questions into semantic models, curated datasets and reusable data assets that leaders across EMEA and APAC rely on, working with our engineers on the upstream design that keeps those assets scaling, and getting them ready for agentic and AI-led delivery. If you want work that carries real weight, we would like to hear from you.

Design, build, and maintain semantic models and curated datasets on the Databricks platform, ensuring they are performant, reusable, and aligned with governance standards. Act as the technical bridge between the central Data Engineering team and transformation/business stakeholders, translating ambiguous business questions into structured data models. Build and maintain automation/AI-readiness scoring frameworks — turning taxonomy and process data into structured, defensible metrics used in executive business cases. Produce the quantitative backbone of transformation business cases: current-state baselines, savings and benefit tracking, scenario/what-if models, and before/after comparisons. Standardise datasets and business logic so that transformation workstreams (cost optimisation, resourcing, margin analysis) build consistently on a shared foundation rather than one-off extracts. Collaborate with the data engineering team on the design of upstream data assets, ensuring they meet the requirements of scalable, transformation-facing analytics. Contribute to data assets and pipelines that are structured to support AI, machine learning, and agentic workflows — increasingly the default mode of delivery rather than a side project. Monitor and optimise the performance of data models and semantic layers, proactively identifying and resolving data quality issues before they reach executive reporting. Support platform adoption through documentation, standards, and knowledge transfer, contributing to best practices for data modelling, naming conventions, and dataset