Data Engineer, VP
Join us as a Data Engineer
- You’ll be the voice of our customers, using data to tell their stories and put them at the heart of all decision-making
- We’ll look to you to drive the build of effortless, digital first customer experiences
- If you’re ready for a new challenge and want to make a far-reaching impact through your work, this could be the opportunity you’re looking for
- We're offering this role at vice president level
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 ETL 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.
Your responsibilities will also include:
- Building advanced automation of data engineering pipelines through removal of manual stages
- Embedding new data techniques into our business through role modelling, training, and experiment design oversight
- Delivering a clear understanding of data platform costs to meet your departments cost saving and income targets
- Sourcing new data using the most appropriate tooling for the situation
- Developing solutions for streaming data ingestion and transformations in line with our streaming strategy
The skills you'll need
To thrive in this role, you’ll need to design, develop, and maintain robust, scalable data pipelines using AWS cloud-native services and modern data engineering frameworks to support both batch and real-time streaming workloads, ensuring high availability, performance, and fault tolerance across the data platform.
You'll also establish and govern end-to-end data lineage, metadata management, and data cataloguing capabilities to enable traceability, impact analysis, regulatory compliance, and improved transparency across enterprise data products.
Additionally, you’ll need:
- Define and implement data quality frameworks through automated validation, monitoring, and alerting mechanisms to ensure the accuracy, completeness, consistency, and reliability of critical datasets
- Apply DevOps and DataOps best practices by implementing CI/CD pipelines, automated testing, and deployment processes. Demonstrate a good working knowledge of Infrastructure as Code (IaC) principles and tools such as Terraform to support the delivery and management of data solutions
- Work effectively within AWS-based cloud environments, possessing a solid understanding of core AWS services relevant to data and analytics platforms, including security, monitoring, and operational best practices
- Collaborate with architecture, engineering, and business teams to support the evolution of the Data & Analytics platform, contributing ideas and improvements that enhance scalability, reliability, and operational efficiency
- Evaluate and improve existing data engineering processes, standards, and platform capabilities, helping to drive continuous improvement and adoption of cloud engineering best practices
Hours
45Job Posting Closing Date:
30/07/2026