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Co-operative Bank
Banking + 2 more
Description
Skills, Competencies and Experience
The successful candidate will be required to have the following skills and competencies:
- A Bachelor’s degree in Computer Science, Information Systems, Data Management, Engineering, Statistics, or a related field.
- Professional certification in Data Architecture, Cloud Data Platforms, Data Management, or Enterprise Architecture will be an added advantage.
- Exposure or training in AI, machine learning, analytics, or data governance will be an added advantage.
- A minimum of 5 years’ relevant experience in Data Architecture, Data Engineering, Enterprise Data Management, or Solution Architecture.
- A strong understanding of enterprise data architecture, data modelling, integration architecture, and information management.
- Experience designing data solutions across operational systems, APIs, data warehouses, and analytics environments.
- A strong understanding of data quality, metadata, lineage, cataloguing, and governance practices.
- The ability to translate complex technical data concepts into clear business language.
- Experience working collaboratively across business, architecture, engineering, security, and governance teams.
Responsibilities
- Design and govern scalable, secure, and high-quality data architectures, models, integrations, and pipelines that support AI, analytics, automation, and enterprise data initiatives.
- Drive data governance, quality, lineage, privacy, security, compliance, and audit readiness standards to ensure trusted and compliant AI-enabled decision-making.
- Assess and enhance the Bank’s data landscape by identifying architecture gaps, defining reusable data assets, and supporting AI readiness and continuous improvement.
- Translate business and AI requirements into practical data solutions, architecture standards, mappings, and implementation guidance.
- Collaborate with cross-functional teams, vendors, and stakeholders to support AI solution delivery, architecture reviews, innovation initiatives, and enterprise data best practices.
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