To develop, design and maintain the solution architectures for specific business functional/technical areas. To participate in the definition of the higher-level functional and non-functional requirements, analyse technical trade-offs, determine the major components and subsystems, and define the interfaces and collaborations between them, safeguarding the strategic alignment of technology architecture with the agreed business outcomes.
1. Solution Design & Architecture
Design scalable, secure, and high-performance data solutions aligned with business requirements.
Define data architecture standards, patterns, and best practices.
Lead the selection of appropriate technologies, platforms, and tools for data solutions.
2. Enterprise Data Strategy
Contribute to the development and execution of enterprise data strategies.
Align data architecture with business goals, digital transformation initiatives, and regulatory requirements.
Promote data as a strategic asset across the organization.
3. Data Modeling & Integration
Develop conceptual, logical, and physical data models.
Architect data integration solutions across on-premises and cloud environments.
Ensure data consistency, quality, and lineage across systems.
4. Cloud & Platform Architecture
Design and implement cloud-native data solutions (e.g., Azure, AWS, GCP).
Evaluate and integrate data platforms such as data lakes, data warehouses, and lakehouses.
Optimize data storage, compute, and processing architectures.
5. Governance, Security & Compliance
Embed data governance principles into solution design.
Ensure compliance with data privacy regulations (e.g., POPIA, GDPR).
Implement data security controls, access management, and encryption strategies.
6. Collaboration & Stakeholder Engagement
Work closely with business units, data engineers, analysts, and IT teams.
Translate business needs into technical requirements and data solutions.
Present architectural decisions and roadmaps to senior leadership.
7. Innovation & Continuous Improvement
Stay abreast of emerging technologies and trends in data architecture.
Drive innovation in data engineering, analytics, and AI/ML enablement.
Continuously improve architecture for performance, cost-efficiency, and agility.
8. Mentorship & Leadership
Provide technical leadership and mentorship to data engineering and analytics teams.
Establish architectural review processes and promote knowledge sharing.
Contribute to talent development and capability building in data disciplines.
Qualifications
Type of Qualification:
First Degree
Field of Study:
Information Studies
Other Minimum Qualifications, certifications or professional memberships
Relevant Architecture Certification;
AWS Certification advantageous
TOGAF Frameworks
Experience Required
Information Lifecycle Management
Data & Analytics
5-7 years
Knowledge and experience working with and implementing internationally recognised frameworks; such as TOGAF, Zachman etc. Proven track record of comprehensive analysis and architectural skills to drive delivery of architectural constructs and artefacts in line with business strategy
5-7 years
Proven track record of comprehensive analysis and architectural skills to drive delivery of architectural constructs and artefacts in line with business strategy
Additional Information
Behavioural Competencies:
Adopting Practical Approaches
Articulating Information
Challenging Ideas
Checking Things
Examining Information
Exploring Possibilities
Interacting with People
Meeting Timescales
Producing Output
Providing Insights
Taking Action
Team Working
Technical Competencies:
Data Integrity
IT Applications
Knowledge Classification
Knowledge Management Systems
Systems Design
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