Albany Beck
Data Architecture & Governance Lead
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Data Architecture & Governance Lead
Company: Albany Beck
Location: London / Hybrid
Engagement Type: Permanent
Client Industry: Financial Services
About Albany Beck
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 capabilities should be grounded in authoritative enterprise data and agreed business rules.
- Ensure AI-generated conclusions can be traced back to appropriate source data and evidence.
- Work with AI Engineers and Data Scientists to ensure data structures are suitable for downstream AI consumption.
- Support the development of scalable data foundations rather than bespoke pipelines for individual AI use cases.
- Work directly with Product Owners, Data Engineers, AI specialists, Solution Architects and business stakeholders throughout design and delivery.
- Provide senior data leadership and challenge across the existing delivery team.
- Review technical outputs and ensure appropriate standards are maintained.
- Resolve architectural and governance constraints before they become significant delivery blockers.
- Support solutions through design, build, testing and approval rather than operating solely as a documentation-focused architect.
- Communicate complex data and architecture decisions clearly to both technical and non-technical stakeholders.
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Key Skills & Experience
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- Significant experience within Data Architecture, Data Governance or senior enterprise Data roles.
- Strong understanding of enterprise data architecture principles, patterns and standards.
- Proven experience navigating complex architecture and data governance approval processes within large organisations.
- Experience taking data designs through architecture/design boards and securing formal approval.
- Strong experience developing and reviewing ERDs, data models, data relationships and integration designs.
- Ability to translate business processes and requirements into strategic data solutions.
- Experience identifying and leveraging existing enterprise architecture patterns.
- Strong understanding of data lineage, data quality, metadata, ownership and governance.
- Experience designing solutions across complex legacy and modern data environments.
- Knowledge of Oracle, SQL, MongoDB, APIs and ETL/integration patterns.
- Strong understanding of data security, classification, access and retention requirements.
- Experience providing design assurance and quality oversight to Data Engineering teams.
- Strong stakeholder management skills across Data, Architecture, Technology and business functions.
- Experience within large, highly governed and regulated organisations.
Desirable Experience
- Banking or Financial Services experience.
- Third-Party Risk Management, Supplier Risk or Vendor Management experience.
- Experience with Business Continuity Planning, Exit Planning, Disaster Recovery or Operational Resilience.
- Exposure to AI, Generative AI or Machine Learning programmes.
- Experience designing data architecture to support AI or advanced analytics capabilities.
- Understanding of AI grounding, data provenance and traceability.
- Experience working with structured and unstructured datasets.
- Exposure to cloud-based enterprise data platforms.
- Experience supporting major regulatory or enterprise transformation programmes.
Personal Attributes
- Strategic thinker who can also operate at a detailed delivery level.
- Strong governance mindset without unnecessarily slowing delivery.
- Comfortable challenging proposed solutions and technical complexity.
- Able to identify pragmatic ways of navigating complex enterprise governance.
- Confident engaging with senior Architecture, Data and Technology stakeholders.
- Strong attention to detail with the ability to identify weaknesses in data designs and standards.
- Proactive in identifying potential architectural and governance blockers.
- Collaborative and comfortable providing leadership without directly managing technical teams.
- Delivery-focused and willing to remain engaged through design, build and implementation.
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