Senior Data Architect

Join us at Barclays as a Senior Data Architect. We are seeking a highly experienced and forward‑thinking Senior Data Architect to lead the design, evolution, and governance of our enterprise data landscape. This is a pivotal role where you will shape data strategy, define architectural standards, and ensure our platforms are scalable, resilient, and aligned with business goals.

• Lead enterprise data architecture decisions, defining standards, principles, and reference architectures that balance performance, scalability, and resilience.
• Deep expertise in cloud data architecture and distributed computing paradigms
  , with strong hands‑on background in AWS data platforms
  , including Glue, Lambda, S3, Redshift, Athena
  , and Databricks
  .
• Implement modern architectural patterns including Lakehouse and event‑driven architectures to support diverse data use cases.
• Establish and enforce data modelling standards across conceptual, logical, and physical layers, ensuring consistency and reusability.
• Enable the delivery of high‑quality, analytics‑ready data assets across the organisation.

• Experience leading Dev Ops and CI/CD strategies for data platforms, using tools such as Jenkins and Git Lab to embed automation, quality, and reliability into pipelines.
• Strong understanding of data governance, metadata management, data quality frameworks, and data mesh concepts, with the ability to drive enterprise‑wide adoption.
• Experience supporting machine learning and AI workloads, including model training, inference pipelines, or feature engineering, in collaboration with Data Science or AI teams.

This role is based in London

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job‑specific technical skills.

To define, direct and govern the bank’s target data architecture (inc. shared data environment, data model and standards) in support of business strategy, ensuring that data is accurate, secure and accessible to meet the needs of stakeholders.

• Development of the banks data architecture strategy, including the translation of bank‑wide goals and objectives into target data architecture and transition plan.
• Collaboration with stakeholders, including data operations, engineers and analysts, to provide subject matter expertise and share knowledge to promote standardised, consistent, safe and value‑driven data usage.
• Development and maintenance of the banks data architecture governance, standards and protection policies, regarding data models, authoritative data stores, and data capabilities, to support data quality, accuracy and consistency and the protection of sensitive information.
• Management of the alignment of projects to the target data architecture through the provision of guidance, data solutions and monitoring of progress.
• Definition of the shared reusable data capabilities, assets, tools and technologies required to connect disparate data sources, optimise data storage and provide seamless data access.
• Custodianship of an overarching data model that directs how data is logically and physically structured within the banks physical data resources, e.g. database, interfaces and reports.
• Monitoring applicable regulatory standards and industry developments for potential impact on the banks operations, controls and application portfolio.
• Identification and selection of best‑in‑class data technologies and ongoing assessment of compliance with the bank’s service level agreements and quality standards.