Manager: Data Transformation and Platforms

Belay Talent Solutions; Johannesburg; On-site; ZAR 1,000,000 - 1,850,000; Full time

Job summary

Belay Talent Solutions seeks a Manager: Data Transformation & Platforms on a 12-month fixed term contract to lead the modernisation, implementation, and operation of the enterprise data platform, enabling digital transformation, advanced analytics, AI, pricing optimisation, and data-driven decision-making.

You will define architecture, modernise legacy environments, drive cloud-based platforms, govern data quality and privacy, and build high-performing cross-functional teams while managing

Qualifications

• 5-7 years' experience in data engineering, data platforms, enterprise architecture, or related disciplines.
• Experience building or modernising enterprise data platforms.
• Experience with cloud technologies, platform engineering, and legacy system integration.
• Valid drivers license.

Responsibilities

• Define and execute enterprise data platform strategy and architecture.
• Modernise legacy data environments and establish scalable cloud-based platforms.
• Lead data integration, engineering, platform delivery, and automation initiatives.
• Implement data governance, quality, privacy, metadata, and lineage standards.
• Enable trusted enterprise data, self-service analytics, and AI-driven capabilities.
• Collaborate with business and technology stakeholders to align data initiatives with strategic priorities.
• Manage platform vendors, delivery partners, budgets, and resources.
• Build, lead, and develop high-performing data and platform teams.

Skills

Data engineering

Enterprise architecture

Platform engineering

Cloud technologies

Leadership

Team management

Data governance

Education

NQF Level 7 qualification in IT, Computer Science, Engineering, or a related field

Tools

TOGAF

Azure

AWS

GCP

Job description

Manager:Data Transformation & Platforms (12 month Fixed Term Contract)

Lead the modernisation, implementation, and operation of the enterprise data platform to enable digital transformation, advanced analytics, AI, pricing optimisation, and data-driven decision-making. Ensure trusted, scalable, and accessible data capabilities that support business growth and operational excellence.

Key Responsibilities:

• Define and execute enterprise data platform strategy and architecture.
• Modernise legacy data environments and establish scalable cloud-based platforms.
• Lead data integration, engineering, platform delivery, and automation initiatives.
• Implement data governance, quality, privacy, metadata, and lineage standards.
• Enable trusted enterprise data, self-service analytics, and AI-driven capabilities.
• Collaborate with business and technology stakeholders to align data initiatives with strategic priorities.
• Manage platform vendors, delivery partners, budgets, and resources.
• Build, lead, and develop high-performing data and platform teams.

Minimum Requirements:

• NQF Level 7 qualification in IT, Computer Science, Engineering, or a related field.
• 5-7 years' experience in data engineering, data platforms, enterprise architecture, or related disciplines.
• Experience building or modernising enterprise data platforms.
• Experience with cloud technologies, platform engineering, and legacy system integration.
• Proven leadership of technical delivery teams.
• Valid driver's licence.

Preferred Requirements:

• NQF Level 8 qualification.
• Cloud Data Engineering certifications.
• Architecture certifications (TOGAF, Azure, AWS, GCP).
• Experience in mobility, financial services, or asset-intensive industries.
• Exposure to AI and advanced analytics initiatives.

Key Challenges:

• Modernising complex legacy data environments.
• Balancing business priorities with long-term platform transformation.
• Establishing enterprise-wide data governance and ownership.
• Building data engineering capability in a competitive talent market.
• Maintaining operational continuity while delivering transformation initiatives.

Decision-Making Authority:

• Data platform architecture, standards, and technology selection.
• Platform investment prioritisation and roadmap sequencing.
• Integration and modernisation approaches for legacy systems.
• Build-versus-buy decisions for data and analytics solutions.
• Resource allocation and platform delivery trade-offs.

Key Stakeholders:

Internal: Executives, Product Teams, IT, Data & Analytics Teams
External: Technology Vendors, Implementation Partners