OM Bank - Data Architect

Requirements

• Competencies
• Action Oriented
• Business Insight
• Cultivates Innovation
• Drives Results
• Ensures Accountability
• Manages Complexity
• Optimizes Work Processes
• Persuades
• Education
• Bachelors Degree (B)
• Closing Date
• 03 June 2026 , 23:59
• The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific

Benefits

Additional Information

Let's Write Africa's Story Together! Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this. Job Description At OM Bank, we strive to attract great people who are passionate about coming together for a higher purpose- building something unique and aspirational, always aiming to be the best they can be. We are rooted in our purpose of inspiring and enabling our customers to grow and sustain their prosperity. The Data Architect applies enterprise-level frameworks, standards, and best practices-set by the Data Architect & Modeller Lead and defined by the Enterprise Data Architect-to domain-level or project-specific data solutions. Operating within the organisation's data-driven, compliance-focused digital banking environment, the Data Architect ensures that data architectures meet business needs, align with data governance directives, and uphold regulatory requirements. This role involves translating high-level reference architectures into actionable conceptual and logical data designs that support accurate and timely risk data aggregation, enable advanced analytics (including AI/ML), and promote data quality, lineage, and security at the implementation level. KEY RESULT AREAS Domain-Level Architecture & Compliance: Develop conceptual and logical data architectures for specific domains, squads, or projects, adapting enterprise frameworks to local needs while ensuring alignment with governance standards and regulatory obligations. Integrate data quality metrics, lineage tracking, metadata standards, and privacy/security controls into data architectures, ensuring that solutions can reliably support risk data aggregation and timely reporting as mandated by international banking guidelines. Collaboration & Documentation: Work closely with Data Modellers, providing detailed architectural artifacts (architecture artefacts, diagrams, data flows) to guide the creation of logical and physical data models. Collaborate with Data Engineers, Data Governance teams, and other stakeholders to clarify architectural intent, resolve technical challenges, and ensure that resulting data solutions are both compliant and optimised for performance, scalability, and cost efficiency. Continuous Improvement & Adaptability: Take part in proofs of concept (POCs), pilot projects, and sandbox initiatives to test and refine architectural approaches, ensuring flexibility and adaptability to evolving risk reporting requirements and emerging technologies. Identify opportunities to improve domain-level architectures based on feedback from squads, changes in regulatory landscapes, advancements in analytics tools, or shifting business priorities. ROLE REQUIREMENTS Bachelor's degree in Computer Science, Informatics, Information Systems, or a related field Minimum of 6-8 years experience in data architecture, data warehousing, cloud-based BI solutions, and an understanding of data governance and regulatory frameworks in a banking or similarly regulated environment. Demonstrated ability to balance technical optimisation with governance and compliance imperatives, ensuring data lineage, quality, and security are integral to architectural designs. Strong communication, problem-solving, and collaborative skills to work effectively with technical teams, governance stakeholders, and business units. Competencies & Skills: Data Architecture & Modelling Techniques (Conceptual/Logical) Alignment with Governance, Data Quality, and Regulatory Standards Performance, Scalability & Cost Optimisation Focused Effective Communication & Cross-Functional Collaboration Adaptability to Evolving Risk Management and Compliance Demands What Success Looks Like: Well-structured, domain-level architectures that are easily translated into high-quality data models, enabling accurate, timely risk data aggregation and advanced analytics use cases. Positive feedback from Data Modellers, Data Engineers, and governance stakeholders on the clarity, completeness, and compliance-readiness of provided architectural artifacts. Continuous refinement and improvement of domain-level architectures, keeping pace with new regulatory requirements, data governance practices, and emerging technologies.

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