Director of Data Engineering leading data architecture and analytics at Petfolk. Overseeing data infrastructure and managing a data team to drive AI and business intelligence solutions.
About the role
- Data Engineering Lead at Absa enabling analytics and AI through scalable data platforms. Overseeing engineering teams to deliver high-quality, trusted data solutions.
Responsibilities
- Accountable for shaping and advising on the IT functional operating model to introduce and scale enterprise data platforms.
- Leads engineering teams while defining platform patterns, standards, and architectures.
- Ensures cross-discipline integration (data, engineering, cloud, platforms, architecture, security) and alignment to enterprise strategy.
- Influences executive decision making through evidence based recommendations, setting direction for enterprise data pipelines, platforms, and reusable shared data assets consumed across the organisation.
Requirements
- NQF Level 8 qualification/Postgraduate degree in Computer Science, Data/Software Engineering, Mathematics, Statistics, or a related quantitative discipline.
- Master’s or PhD in a relevant field (Data Engineering, Computer Science, Applied Mathematics, Econometrics, or similar).
- Certifications in cloud or data engineering advantageous (e.g., Azure DP‑203, Databricks Data Engineer, AWS/GCP Data certifications, SAFe, TOGAF, CNCF).
- 12–15+ years in data engineering, enterprise data platforms, or data warehousing, with 5+ years leading and managing engineering teams delivering at enterprise scale.
- Demonstrated success designing, building, and operating production-grade batch and streaming data pipelines, with strong DataOps, observability, and lifecycle management.
- Proven experience in regulated environments (financial services advantageous), including privacy, records management, and audit requirements.
Benefits
- Professional certifications advantageous (cloud, data engineering, architecture)
- Evidence of continuous learning in modern data engineering, cloud-native architectures, streaming/CDC, observability, DataOps, and governed data sharing.
- Champion responsible data practices, ethical data use, and secure data sharing.
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