Data Engineer, Analytics Engineering
Data Engineer in Royal Bank of Scotland's Private Banking & Wealth Management unit, building canonical and semantic data layers and governed analytics data products on a cloud platform. Day to day: SQL data modelling (Iceberg on AWS), building pipelines, and defining data quality, SLAs, and governance with stakeholders.
- Compensation
- Not disclosed
- Location
- City of Edinburgh, United Kingdom
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong understanding of data usage and dependencies; experience extracting value and features from large-scale data
- Practical experience with programming languages and knowledge of data and software engineering fundamentals
- Significant experience as an Analytics Engineer, BI Engineer, or Data Architect in complex, data-rich environments
- Proven track record managing governed data products with clear ownership, SLAs, documentation, and quality control
- Track record designing canonical data models standardising entities across systems/domains and semantic layers for different audiences
- Excellent SQL and data modelling skills on modern formats like Iceberg on AWS, with large and complex cloud datasets
- Hands-on experience with transformation-as-code, testing, version control, and automated deployment
- Ability to communicate complex data concepts simply and lead workshops with non-technical stakeholders
Full description
Join us as a Data Engineer, Analytics Engineering
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
What you'll do
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.
Your responsibilities will also include:
- Working with business stakeholders to understand their needs and translate them into intuitive canonical and semantic data models
- Designing and evolving standardised, cross domain data models such as party, account, deposit, mortgages that align with our enterprise data model
- Building and maintaining governed analytical data products, ensuring they are well documented, discoverable, and consistently used across teams
- Defining and implementing data quality checks, SLAs, and governance practices so that our data is accurate, reliable, and compliant
- Collaborating with data architects, engineers, BI teams and data scientists to ensure models are scalable, performant, and easy to consume on our cloud data platform
The skills you'll need
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.