Data Engineer, VP

• You'll be helping to build the next generation of AI-powered customer and colleague experiences through data, knowledge and intelligent automation.
• We'll look to you to develop scalable data, content and knowledge engineering capabilities that support Conversational AI, Knowledge Studio, AI Knowledge Bases and other strategic AI initiatives.
• If you're ready for a new challenge and want to shape the future of Generative AI and knowledge-driven experiences across the bank, this could be the opportunity you're looking for.
• We're offering this role at vice president level

As a Data Engineer, you'll help design, build and operate the data and knowledge engineering capabilities that power our strategic AI platforms. You'll be responsible for developing scalable data, content and knowledge pipelines that transform enterprise information into AI-ready assets for consumption by conversational AI solutions, knowledge platforms, AI agents and other intelligent services.

You'll work across the end-to-end lifecycle of data and knowledge processing, from ingestion and transformation through to retrieval, governance and AI consumption. You'll collaborate closely with architects, engineers, data scientists and business stakeholders to develop reusable platforms and services that support innovation while ensuring our data and knowledge assets remain secure, governed and trusted.

You'll drive customer and colleague value by understanding complex business challenges and applying modern engineering practices to build scalable, reusable and cloud-native solutions.

Your responsibilities will also include:

• Building and maintaining automated data, content and knowledge ingestion pipelines from enterprise repositories and digital channels.
• Developing solutions to transform documents and unstructured content into AI-ready formats including metadata enrichment, content segmentation and knowledge preparation.
• Designing and implementing retrieval, indexing and vectorisation pipelines to support Generative AI and Retrieval-Augmented Generation (RAG) solutions.
• Integrating knowledge and AI services with AWS platforms including Amazon Bedrock and SageMaker Unified Studio.
• Building advanced automation capabilities by removing manual processing activities and improving operational efficiency.
• Developing APIs, reusable services and event-driven solutions to support Knowledge Studio, Conversational AI and AI-powered customer journeys.
• Implementing controls for data quality, knowledge quality, governance, PII detection and regulatory compliance.
• Delivering monitoring, observability and operational controls for data and AI platforms.
• Supporting experimentation, innovation and implementation of emerging AI technologies and AI engineering practices.
• Contributing to architecture, engineering standards and best practices across data and AI platforms.
• Developing solutions for batch, streaming and event-driven data ingestion and transformations in line with strategic technology direction.
• Working collaboratively across engineering, architecture, product and business teams to deliver enterprise-scale AI solutions.

To thrive in this role, you'll need a strong understanding of data engineering, software engineering and cloud-native technologies, alongside experience building scalable solutions for structured and unstructured data.

You'll bring practical experience of modern programming languages, cloud services and engineering practices, together with a passion for emerging AI technologies and data-driven innovation. You 'll have an experience of 12+ years in the below mentioned skillsets

Additionally, you'll need:

Essential Skills & Experience

• Strong experience in Python and SQL development.
• Experience designing and building ETL/ELT pipelines and data processing frameworks.
• Hands-on experience with AWS cloud services and cloud-native solution development.
• Experience working with: Amazon Bedrock SageMaker Unified Studio Amazon S3 AWS Lambda AWS Glue DynamoDB ECS/Fargate Step Functions EventBridge OpenSearch
• Experience building REST APIs and microservices.
• Strong understanding of data engineering fundamentals, data modelling and data architecture principles.
• Experience working with structured and unstructured data.
• Experience with modern software engineering practices including Git, GitLab, CI/CD and automated testing.
• Knowledge of data quality frameworks, monitoring and observability.
• Experience working in a governed and regulated environment.
• Strong communication skills with the ability to proactively engage and manage a wide range of stakeholders.

Preferred Skills & Experience

• Experience with Generative AI technologies and Large Language Models (LLMs).
• Understanding of Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval concepts.
• Experience working with embeddings, semantic search and vector databases.
• Knowledge of document transformation, content processing and knowledge engineering practices.
• Experience building knowledge management, content ingestion or AI-driven information platforms.
• Building and maintaining automated data, content and knowledge ingestion pipelines from enterprise repositories and digital channels.
• Developing solutions to transform documents and unstructured content into AI-ready formats including metadata enrichment, content segmentation and knowledge preparation.
• Designing and implementing retrieval, indexing and vectorisation pipelines to support Generative AI and Retrieval-Augmented Generation (RAG) solutions.
• Integrating knowledge and AI services with AWS platforms including Amazon Bedrock and SageMaker Unified Studio. 

Hours

Job Posting Closing Date: