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Join us at Barclays as a Vice President - Data Architect. In this role, you will play a key part in shaping and evolving our data architecture strategy, helping to enhance our trading applications across the organization enabling consistency, scalability, and better decision making across teams.
Job Responsibility
Analysis and documentation of business requirements to translate them into data models aligned with organisational goals.
Development and maintenance of data dictionaries and glossaries to define data elements and their usage.
Analysis and monitoring of data usage patterns to identify opportunities for data optimisation and improvement, in partnership with the Data Base Administrator.
Strategic architecture definition and product selection.
Production of logical designs in relevant subject area (technical, data, operational), showing for example: processes, objects, data flows, inputs, stored data and outputs. Identifying common components.
Implementation of architectures and Identification, ownership and resolution of design related issues.
Definition and documentation of data architectures standards, principles and strategies.
Requirements
Investment Banking, including Financial Markets, Expertise
Strong understanding of Investments Banking and Financial Markets, including end-to-end trade lifecycles, market structures, and the flow of data across front‑to‑back processes (from client onboarding, trade capture through post-trade processing).
Enterprise Data Modelling & Architecture Leadership
Proven experience designing and driving adoption of unified data models (e.g., Client, Banking & Trade data representation), including shaping proposals and supporting their implementation across complex environments.
Advanced Data Architecture Capability
Deep expertise in data architecture disciplines, including: Data flow design
Logical and physical data modelling
Translating business and data requirements into scalable, implementable solutions
Engineering Collaboration & Delivery Enablement
Ability to work closely with engineering teams to deliver architectural outcomes across both upstream (trade capture) and downstream (post-trade) systems, ensuring alignment between design and implementation.
End-to-End Stakeholder Engagement
Strong stakeholder management skills, including: Engaging with business and technical teams to understand current-state trade capture and processing
Partnering across the value chain to drive alignment and adoption of data architecture standards.