The Co-operative Bank of Kenya Limited is incorporated in Kenya under the Company Act and is also licensed to do the business of banking under the Banking Act. The Bank was initially registered under the Co-operative Societies Act at the point of founding in 1965. This status was retained up to and until June 27th 2008 when the Banks Special General Meeti...

The Role

Specifically, the successful jobholder will be required to:

• Define the target architecture and transition roadmap for the Bank’s enterprise data platforms, including data warehouses, data lakes or lakehouses, real-time streaming capabilities, integration patterns and consumption layers, within the approved enterprise architecture.
• Design conceptual, logical and physical data models for priority data products, analytical solutions and AI use cases, with clear definitions, ownership and quality requirements.
• Define architecture patterns for data ingestion, storage, transformation, sharing, retention, archival and deletion across batch, streaming and real-time use cases.
• Partner with business data owners and Data Governance teams to establish common definitions, metadata, lineage, master and reference data requirements and authoritative sources.
• Guide Data Engineers in implementing scalable, reusable and governed data products, ensuring traceability from source to consumption, rationalising legacy data stores, reducing unnecessary duplication and defining migration approaches towards the target-state data platform.
• Ensure data designs incorporate security classification, access control, privacy, segregation, encryption, retention, resilience and regulatory requirements by design, including compliance with the Data Protection Act, 2019.
• Review data solution designs and proposed changes to source systems for data impact, represent data architecture at the Architecture Review Board, document architecture decisions and exceptions, and ensure identified risks and technical debt have accountable owners and agreed remediation plans.
• Maintain enterprise data models, data cataloguing requirements and architecture artefacts, and provide technical guidance to delivery squads, Data Engineers, Data Scientists, the AI and Data Architect, business data owners and other stakeholders.

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, Mathematics or a related field.
• A relevant master’s degree is an added advantage.
• Professional certification in data management, data architecture, enterprise architecture or cloud data platforms is an added advantage.
• At least seven (7) years of experience in data management, data engineering, database design, analytics or architecture, including at least three (3) years in data architecture or a senior data modelling role.
• Demonstrated experience designing enterprise data models and modern analytical data platforms.
• Experience in banking, financial services or another data-intensive regulated environment is preferred.
• Conceptual, logical and physical data modelling.
• Data warehousing, lakehouse, data lake and data product patterns.
• Metadata, lineage, master and reference data, and data quality.
• Batch, streaming and real-time data architecture.
• SQL and relational and non-relational data technologies.
• Privacy, security, records retention and resilience by design.
• Data architecture governance and design review.
• Communication with business data owners and technical teams.
• Flexibility to work across business and technology teams and to support critical delivery or production activities when required.
• Commitment to confidentiality, responsible use of data and AI, and compliance with the Bank’s policies and control requirements.

• Define the target architecture and transition roadmap for the Bank’s enterprise data platforms, including data warehouses, data lakes or lakehouses, real-time streaming capabilities, integration patterns and consumption layers, within the approved enterprise architecture.
• Design conceptual, logical and physical data models for priority data products, analytical solutions and AI use cases, with clear definitions, ownership and quality requirements.
• Define architecture patterns for data ingestion, storage, transformation, sharing, retention, archival and deletion across batch, streaming and real-time use cases.
• Partner with business data owners and Data Governance teams to establish common definitions, metadata, lineage, master and reference data requirements and authoritative sources.
• Guide Data Engineers in implementing scalable, reusable and governed data products, ensuring traceability from source to consumption, rationalising legacy data stores, reducing unnecessary duplication and defining migration approaches towards the target-state data platform.
• Ensure data designs incorporate security classification, access control, privacy, segregation, encryption, retention, resilience and regulatory requirements by design, including compliance with the Data Protection Act, 2019.
• Review data solution designs and proposed changes to source systems for data impact, represent data architecture at the Architecture Review Board, document architecture decisions and exceptions, and ensure identified risks and technical debt have accountable owners and agreed remediation plans.
• Maintain enterprise data models, data cataloguing requirements and architecture artefacts, and provide technical guidance to delivery squads, Data Engineers, Data Scientists, the AI and Data Architect, business data owners and other stakeholders.

• Conceptual, logical and physical data modelling.
• Data warehousing, lakehouse, data lake and data product patterns.
• Metadata, lineage, master and reference data, and data quality.
• Batch, streaming and real-time data architecture.
• SQL and relational and non-relational data technologies.
• Privacy, security, records retention and resilience by design.
• Data architecture governance and design review.
• Communication with business data owners and technical teams.
• Flexibility to work across business and technology teams and to support critical delivery or production activities when required.
• Commitment to confidentiality, responsible use of data and AI, and compliance with the Bank’s policies and control requirements.

• A bachelor’s degree in Computer Science, Information Systems, Data Management, Engineering, Mathematics or a related field.
• A relevant master’s degree is an added advantage.
• Professional certification in data management, data architecture, enterprise architecture or cloud data platforms is an added advantage.
• At least seven (7) years of experience in data management, data engineering, database design, analytics or architecture, including at least three (3) years in data architecture or a senior data modelling role.
• Demonstrated experience designing enterprise data models and modern analytical data platforms.
• Experience in banking, financial services or another data-intensive regulated environment is preferred.