Head Engineering (CDAO

A leading organisation is seeking a Head: Data Engineering to lead and industrialise the engineering capability supporting its retail banking data environment. This senior leadership role will shape modern data foundations, strengthen governance and enable reliable data products for analytics, MI/BI, AI, data science and customer-led decision-making.

Responsibilities:

• Define and lead the engineering strategy and roadmap across enterprise data warehousing, data lakes, ingestion, curation, semantic layers and metadata.
• Modernise fragmented and legacy data environments into integrated, governed and reusable data products.
• Lead the delivery and optimisation of scalable pipelines, warehouse solutions and curated datasets across multiple banking domains.
• Embed data quality, lineage, security, privacy, access control and regulatory compliance throughout the delivery lifecycle.
• Introduce modern engineering practices across Databricks, cloud platforms, DevOps, DataOps, MLOps, automation and AI-assisted curation.
• Drive operational stability, observability and resilience while reducing manual effort and improving delivery times.
• Lead distributed engineering teams, build succession depth and develop a high-performance learning culture.
• Influence senior stakeholders across business, technology, architecture, risk, governance and analytics functions.

Requirements:

• A relevant postgraduate qualification or equivalent experience in Computer Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, Analytics or a related field.
• Significant leadership experience in data engineering, enterprise data warehousing, data lakes, analytics engineering or data-platform delivery within a complex enterprise environment.
• Proven experience delivering large-scale, multi-domain data foundation or warehouse programmes, preferably within banking or financial services.
• Strong knowledge of integrated data modelling, ingestion, curation, metadata, semantic definition, data quality and governance.
• Experience with modern cloud data platforms, Databricks, AWS, deployment automation, DevOps, MLOps and feature stores.
• Sound understanding of POPIA, tokenisation, access management, retention, lineage and audit requirements.
• Exceptional strategic leadership, stakeholder influence, commercial judgement and execution skills.\
• Relevant cloud, architecture, data governance, agile, DevOps or AI/MLOps certifications would be advantageous.

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All positions will be filled in accordance with the company's Employment Equity plan. We encourage people with disabilities to apply.

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REF: PG01