To develop and maintain complete data architecture across several application platforms, provide capability across application platforms. To design, build, operationalise, secure and monitor data pipelines and data stores to applicable architecture, solution designs, standards, policies and governance requirements thus making data accessible for the evaluation and optimisation for downstream use case consumption. To execute data engineering duties according to standards, frameworks, and roadmaps
Minimum Qualifications
Type of Qualification: First Degree
Field of Study: Business Commerce
Type of Qualification: First Degree
Field of Study: Information Studies
Type of Qualification: First Degree
Field of Study: Information Technology
Experience Required
Software Engineering
Technology
5-7 years
- 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 cloud technologies and platforms such as AWS, Azure or GCP. Experience in programming languages such as Python, Java, or C++.
8-10 years
- 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.
- Experience in using Big Data platforms such as Hadoop.
Behavioral Competencies:
- Adopting Practical Approaches
- Articulating Information
- Checking Details
- Developing Expertise
- Documenting Facts
- Embracing Change
- Examining Information
- Interpreting Data
- Managing Tasks
- Producing Output
- Taking Action
- Team Working
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- Data Quality
- IT Knowledge
- Stakeholder Management (IT)
