SPECIALIST DATA ARCHITECTURE

Job purpose

The Specialist Data Architecture is responsible for designing, implementing, and governing the bank's enterprise data architecture to support the bank’s Data Maturity journey. The role ensures that data is structured, managed, and utilized efficiently to drive business value. The Data Architect will play a key role in enabling Master Data Management (MDM), Data Governance, Data Quality, Metadata Management, Advanced Analytics, and Data Security, ensuring alignment with the bank’s strategic objectives. Furthermore, the role owner is expected to define data models, data standards, integration patterns, and data pipelines to enhance enterprise-wide data accessibility, consistency, and security while supporting regulatory compliance and innovation through data-driven decision-making.
Principal responsibilities
Design and implement the Bank’s Enterprise Data Architecture to optimize data accessibility, interoperability, and efficiency across business functions.
Develop and enforce data modelling and data design standards (conceptual, logical, and physical) to ensure consistency across structured and unstructured data assets.
Lead data integration strategy and execution, ensuring seamless connectivity between core banking systems, enterprise data warehouses, data lakes, and cloud platforms.
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Establish and maintain metadata management frameworks, including data catalogs, data dictionaries, and lineage tracking for improved data transparency and governance.
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Define and operationalize enterprise-wide Data Quality frameworks, embedding automated validation, profiling, and monitoring mechanisms to enhance data reliability.
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Ensure compliance with regulatory and security requirements, including data classification, encryption, access controls, and data retention policies.
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Architect scalable and cost-efficient data environments that support current and future business needs while ensuring optimal performance.
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Enable AI, Advanced Analytics, and Self-Service BI platforms by ensuring data readiness, accessibility, and governance for predictive analytics and AI/ML models.
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Continuously assess and integrate emerging data technologies and frameworks, including Data Mesh, Data Fabric, and DataOps, to drive innovation and efficiency.
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Collaborate with business and IT teams to provide expert guidance on data-related initiatives, ensuring alignment with enterprise data strategy and digital transformation goals.