Group Data & AI Leader for Enterprise Transformation

Pronel Consultants; Cape Town; On-site; ZAR 1,800,000 - 3,200,000; Full time

Job summary

Pronel Consultants is seeking a Group Data & AI Manager in Cape Town to architect and lead enterprise data strategy, AI adoption, and information governance. This executive will drive cross-functional delivery across manufacturing, finance and operations, delivering tangible ROI and value realization.

The role requires shaping data platforms, analytics, and governance while partnering with C-suite leaders to identify transformative opportunities and build practical roadmaps for scalable data and

Qualifications

• Experience leading enterprise Data, AI, Analytics and Integration initiatives.
• Strong background in manufacturing or industrial environments.
• Excellent stakeholder management with executive-level influence.
• Ability to develop ROI models and digital roadmaps.

Responsibilities

• Lead strategy and execution of the Group Data & AI agenda to enable data-driven decisions.
• Build and govern enterprise data platforms and analytics capabilities.
• Drive AI, Generative AI and automation initiatives with measurable outcomes.
• Establish governance, reporting standards and KPI frameworks across units.
• Partner with executives to identify high-value digital opportunities and deliver roadmaps.

Skills

Data strategy

AI leadership

Analytics

Stakeholder management

Data governance

Enterprise integration

Education

IT/CS degree

Data/AI certifications

Tools

Azure

Power BI

Snowflake

Qlik Sense

OpenAI APIs

Python

Job description

Pronel Consultants is seeking a Group Data & AI Manager in Cape Town to architect and lead enterprise data strategy, AI adoption, and information governance. This executive will drive cross-functional delivery across manufacturing, finance and operations, delivering tangible ROI and value realization.

The role requires shaping data platforms, analytics, and governance while partnering with C-suite leaders to identify transformative opportunities and build practical roadmaps for scalable data and