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This role is based in the United Kingdom and as such all normal working days must be carried out in the United Kingdom.

Join us as a Data Engineer

• This is an exciting role within our new Data Engineer team within the Colleague Data and Analysis (D&A), supporting the People & Transformation (P&T) teams
• You’ll have the opportunity to shape the creation of a new P&T data warehouse, which is key to supporting our analytics ambitions
• Participating actively in the data engineering community, you’ll deliver opportunities to support our strategic direction while building your network across the bank
• While your team will be based primarily in Edinburgh and Manchester, the remote first nature of the role means you can be based anywhere in the UK

What you'll do

In your new role, you’ll shape the creation of a new P&T data warehouse, with an initial focus on our colleague and people data. You’ll use your knowledge of Workday and other hR systems and data models to drive its development.

We’ll look to you to drive value for the customer through modelling, sourcing and data transformation. You’ll be working closely with core technology and architecture teams to deliver strategic data solutions, while driving Agile and DevOps adoption in the delivery of data engineering.

We’ll also expect you to be:

• Delivering the automation of data engineering pipelines through the removal of manual stages
• Developing comprehensive knowledge of the bank’s data structures and metrics, advocating change where needed for product development
• Educating and embedding new data techniques into the business through role modelling, training and experiment design oversight
• Delivering data engineering strategies to build a scalable data architecture and customer feature rich dataset for data scientists
• Developing solutions for streaming data ingestion and transformations in line with streaming strategy

The skills you'll need

To be successful in this role, you’ll need to be an intermediate level programmer and Data Engineer with a qualification in Computer Science or Software Engineering. You’ll also need a strong understanding of data usage and dependencies with wider teams and the end customer, as well as a proven track record in extracting value and features from large scale data.

You’ll also demonstrate:

• Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modelling and data wrangling
• Extensive experience using RDMS, ETL pipelines, Python, Hadoop and SQL
• A good understanding of modern code development practices
• Good critical thinking and proven problem solving abilities