Data Engineer
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Job Description
To provide technical leadership in the design, delivery, and continuous evolution of enterprise data architecture, data platforms, and AI engineering capabilities. The role enables the organisation to derive value from data by establishing scalable, secure, and governed data foundations, engineering high-quality data products, and supporting advanced analytics, machine learning, and generative AI use cases. The role ensures that all data solutions are aligned to enterprise architecture standards, governance requirements, security controls, and strategic technology objectives while promoting data reliability, interoperability, and operational excellence.
Qualifications
- Type of Qualification: First Degree
- Field of Study: Information Technology, Mathematics, Statistics, Business Commerce or a related discipline
- Relevant professional certifications in cloud data platforms, data architecture, data engineering, data science, machine learning or AI engineering will be an advantage.
Experience Required
8-10years
- Experience in building databases, warehouses, reporting and data integration solutions.
- Experience building and optimising big data data-pipelines, architectures and data sets.
- Experience in creating and integrating APIs. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
- Deep understanding of data pipelining and performance optimisation, data principles, how data fits in an organisation, including customers, products and transactional information. Knowledge of integration patterns, styles, protocols and systems theory
- Experience in database programming languages including SQL, PL/SQL, SPARK and or appropriate data tooling.
- Experience with data pipeline and workflow management tools
Behavioural Competencies:
- Articulating Information
- Developing Expertise
- Interpreting Data
- Managing Tasks
- Producing Output
- Team Working
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- Data Quality
- IT Knowledge
- Stakeholder Management