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Royal Bank of Scotland is hiring a Data Engineer for Analytics Engineering to shape canonical and semantic data layers powering analytics, AI, and reporting for PBWM. You will build trusted data products and govern data assets across the organization.
The role is hands-on with substantial influence on data structure, governance, and consumption. Hybrid work is available with office days in London or Edinburgh.
We're building a brand new Data Products factory capability at the Private Banking & Wealth Management (PBWM) franchise and are looking for a Data Engineer to shape the canonical and semantic data layers that power our Analytics, AI, reporting, and self service capabilities
You'll sit at the heart of our data ecosystem, partnering with Business, Technology and Functions to design clean, reusable data assets from the ground up, and turning them into trusted, governed data products that the business can rely on every day
This is a hands on role with significant influence over how data is structured, governed, and consumed across PBWM
You'll work from home some of the time, but you'll also spend at least twice a week working from our London or Edinburgh office
As a Data Engineer, you'll be looking to simplify our organisation by developing innovative data driven solutions through data pipelines, modelling and design, inspiring to be commercially successful while keeping our customers, and the bank's data, safe and secure.
You'll drive customer value by understanding complex business problems and requirements to correctly apply the most appropriate and reusable tool to gather and build data solutions.
You'll support our strategic direction by engaging with the data engineering community to deliver opportunities, along with carrying out complex data engineering tasks to build a scalable data architecture. In addition, you'll build a strong understanding of our Data Product ecosystem and contribute to the design and delivery of reusable Data Products that support PBWM business and functions.
To thrive in this role, you'll need a strong understanding of data usage and dependencies and experience of extracting value and features from large scale data. You'll also bring practical experience of programming languages alongside knowledge of data and software engineering fundamentals.
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20/10/2026