Data Architecture & Governance Lead

Albany Beck is a Management Consultancy focused on providing specialist talent and transformative solutions to Financial Services clients. We combine subject matter expertise with innovative delivery models that help clients scale efficiently, while offering meaningful, long-term career opportunities to our people. At Albany Beck, you’ll be choosing to work with an organisation that’s passionate about your learning journey and committed to your professional and personal development.

Role Overview

Albany Beck is seeking an experienced Data Architecture & Governance Lead to support a strategic Third-Party Risk Management (TPRM) transformation programme within a leading global banking organisation. The role will take ownership of the data architecture and governance activity supporting a workstream focused on Business Continuity Planning (BCP), Exit Planning and Disaster Recovery (DR), including the development of new AI-enabled capabilities.

This is not a hands-on Data Engineering role. The successful candidate will provide senior data leadership across architecture, governance, design assurance and strategic solutioning, working closely with Data Engineers, AI specialists, Solution Architects, Product Owners and enterprise governance teams. A major focus will be identifying and leveraging existing enterprise data patterns wherever possible, allowing the programme to navigate architectural and data governance approvals efficiently rather than unnecessarily introducing new patterns.

The successful candidate will need to be comfortable operating at both a strategic and tactical level – defining what good looks like, reviewing and challenging proposed solutions, developing data standards and ensuring designs are ready to successfully progress through architecture and governance boards.

Key Responsibilities

• Own the data architecture approach across the TPRM BCP, Exit and DR workstream.
• Review existing data architecture, ERDs, data models and integration designs and provide senior-level design assurance.
• Translate business requirements, processes and decision logic into appropriate data structures, entities and relationships.
• Define strategic and tactical data solutions aligned with wider enterprise architecture.
• Identify opportunities to reuse or extend existing approved data patterns rather than creating unnecessary new architecture.
• Design reusable data products and integration approaches that can support multiple use cases.
• Provide oversight and quality assurance across Data Engineering and wider technical delivery.
• Lead data solutions through internal architecture, design and governance processes.
• Prepare designs and supporting artefacts for architectural and data governance boards.
• Work closely with enterprise Data, Architecture, Technology and Governance teams to secure required approvals.
• Identify the fastest compliant route from business requirement through to approved technical design.
• Ensure solutions meet enterprise standards across data ownership, lineage, classification, access, retention and security.
• Identify governance requirements and potential approval blockers early in the delivery lifecycle.
• Challenge unnecessary complexity and ensure existing strategic patterns are leveraged wherever appropriate.
• Define how data from multiple enterprise sources should be extracted, structured, related and consumed by the target platform.
• Provide architectural oversight across Oracle, SQL, MongoDB, APIs, ETL and associated integration technologies.
• Establish clear data lineage from source systems through transformation and into downstream outcomes.
• Define relationships across supplier, application, service, incident, assessment, contractual and remediation datasets.
• Assess data completeness, accuracy, consistency and fitness for intended use.
• Establish standards and rules against which extracted data can be assessed.
• Identify data gaps and support the definition of pragmatic remediation and treatment plans.
• Support the development of data architecture required for AI-enabled TPRM capabilities.
• Ensure structured and unstructured enterprise data can be reliably accessed and contextualised by AI solutions.
• Define how AI…