Architect, Data Solutions

Job Description

To develop, design and maintain the solution architectures for specific business functional/technical areas within Data and Analytics. 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