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Job Description
Role Overview
The Enterprise Data Architect translates the Data Architect & Modeller Lead's strategic vision and standards into actionable plans for the entire enterprise.
This role creates and maintains the high-level data architecture frameworks, reference models, and guidelines that ensure the bank's data landscapes are consistent, secure, compliant, and capable of supporting advanced analytics, including AI/ML.
The Enterprise Data Architect ensures that all enterprise data solutions can aggregate and report risk data accurately, completely, and in a timely manner.
Although the Data Governance Lead and team define governance policies, the Enterprise Data Architect ensures that these policies and quality standards are integrated into the organisation's data architectures, enabling sustainable compliance with regulatory and risk management requirements.
KEY RESULTS AREAS
Enterprise Frameworks & Standards:
Develop, refine, and maintain enterprise-wide data architecture principles, standards, and reference architectures that align with the strategic vision set by the Data Architect & Modeller Lead.
Ensure these frameworks support effective data lineage tracking, metadata management, data quality controls, and data privacy/security measures.
Incorporate flexibility into the architectures so that the organisation can quickly adapt to evolving regulatory mandates, risk reporting requirements, and emerging technology trends.
Governance, Compliance & Risk Reporting Support:
Embed governance directives from the Data Governance team into enterprise frameworks, ensuring that all architectural standards facilitate data quality, stewardship, and accountability.
Integrate requirements for accurate, timely, and complete risk data aggregation and reporting into data architectures, ensuring compliance with industry regulations and international banking standards.
Evaluate and select technologies, tools, and methodologies that improve the efficiency and reliability of data solutions, including those supporting advanced analytics and AI/ML initiatives.
Collaboration & Knowledge Sharing:
Collaborate with Data Architects, Data Modellers, Solution Architects, and other technical teams to ensure that domain-level solutions and data models are aligned with enterprise frameworks.
Offer guidance, patterns, and templates that squads can use to ensure their data solutions meet governance and compliance standards, as well as performance, scalability, and cost optimisation goals.
Serve as a point of contact and advisor for enterprise-level architecture decisions, promoting best practices and consistency across the organisation's data landscape.
Innovation & Continuous Improvement:
Lead or oversee enterprise-level proofs of concept (POCs), pilot projects, and sandbox initiatives to evaluate emerging data technologies, frameworks, and methodologies.
Assess the feasibility, scalability, and regulatory implications of new data solutions, incorporating successful outcomes into enterprise standards and reference architectures.
Provide guidance and mentorship to Data Architects and Data Modellers, ensuring that lessons learned inform best practices and improve the organisation's overall architectural maturity.
Continuously review and refine enterprise data architectures based on insights gained, focusing on performance optimisation, cost efficiency, compliance, and the ability to rapidly adapt to evolving regulatory and business needs.
REQUIREMENTS & QUALIFICATIONS
Bachelor's degree in Computer Science, Information Systems, or a related field (preferred).
10+ years of experience in BI/Analytics, data architecture, and cloud-based data solutions, with a strong understanding of data governance, privacy, and regulatory frameworks in banking or similar regulated industries.
Demonstrated ability to develop and implement enterprise-scale data architectures that incorporate risk management principles, data lineage, data quality, and advanced analytics capabilities.
Excellent communication, stakeholder management, and influencing skills to align multiple teams under consistent architectural standards.
Competencies & Skills
Enterprise Data Architecture Mastery
Strong Alignment with Governance & Regulatory Requirements
Expertise in Data Quality, Metadata, and Data Lineage Techniques
Adaptability to Emerging Technologies & Evolving Compliance Demands
Collaboration & Influence Across Complex, Matrixed Environments
What Success Looks Like
Clear, cohesive enterprise data architecture frameworks that domain teams can easily apply, resulting in consistent, compliant, and high-quality data solutions.
A data landscape that supports accurate, timely risk data reporting, advanced analytics, and rapid adaptation to changing regulations or business priorities.
Positive feedback from domain architects, modellers, governance leads, and stakeholders on the clarity, reliability, and scalability of the provided enterprise frameworks and guidelines.
Closing Date
20 January 2025 , 23:59
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