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 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.

Additionally, you’ll need:

• Lead the design and delivery of real time data pipelines using Apache Kafka, ensuring low latency, high throughput event streaming across distributed systems
• Experience to architect scalable distributed data processing solutions using Apache Spark (batch + structured streaming) optimized for performance, cost, and resilience
• A good understanding of modern code development practices
• Experience of designing and implementing NoSQL data models like MongoDB, DynamoDB, Cassandra for high-availability, high-volume operational and analytical workloads
• Proficiency in engineering best practices including CI/CD automation, infrastructure as code (Terraform/CloudFormation), testing, observability, and system reliability engineering.
• Collaborate closely with platform, architecture, and product teams to define high-level solution designs (HLSD) and ensure alignment with data strategy and governance