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 languagesalongside knowledge of data and software engineering fundamentals.

Additionally, You’ll Need

• A strong background in building and optimizing pipelines for LLMs, traditional ML models, and data processing pipelines using OSS frameworks or within the AWS/GCP ecosystems
• Strong experience in supervised or unsupervised learning, time‑series forecasting, optimization, feature engineering, model evaluation, and retraining strategies along with RAG, embedding pipelines, LLM orchestration, prompt engineering, and API integration
• Strong proficiency with Python
• Hands on engineering excellence in defining and enforcing standards for ML Ops, CI/CD, experiment tracking, model deployment, observability, security, and performance tuning
• The ability to evaluate and integrate capabilities across OpenAI/Anthropic models, fine‑tuning, GPU compute, AutoML, and feature stores
• A background of working with code repositories, bug tracking tools and wikis