(671) Data Engineer at South African Reserve Bank

Detailed description

The successful candidate will be responsible for the following key performance areas:

• Design and implement data strategies and systems in collaboration with BSTD and business subject matter experts to create and maintain data architecture that drives various FinSurv initiatives.
• Build infrastructure to automate high volumes of data and creatively solve data volumes and scaling challenges.
• Work with team members and other stakeholders to contribute to the design and architecture of innovative solutions to complex problems.
• Collaborate with BSTD to build optimal data extraction, transformation and loading from a wide variety of data sources using big data technologies.
• Assemble large, complex data sets to meet functional and non-functional business requirements.
• Identify, design and implement business process improvements by automating manual processes, optimising data delivery and redesigning infrastructure for greater scalability.
• Provide technical support to the Advanced Analytics Specialist during the design, development and implementation of self-learning applications (artificial intelligence and machine learning).
• Search and select appropriate data sets to run tests, ensuring algorithms generate accurate user recommendations.
• Keep abreast of developments in the industry regarding data engineering practices.

Qualifications

To be considered for this position, candidates must be in possession of:

• a Bachelor’s degree (NQF 7) in Computer Science, Management Information Systems, Computer Engineering or an equivalent qualification;
• five to eight years’ experience in the data engineering field;
• five years’ experience working with relational databases and query authoring (SQL);
• three to five years’ experience building analytics tools using data pipelines; and
• experience with Microsoft Power BI, Tableau, SAS and OBIEE.

The following would be an added advantage:

• programming experience with natural language processing in R, Python and so forth; and 
• relevant programming or data querying certification.

Additional requirements include:

• knowledge and skill in:
• industry, organisational and business awareness;
• data warehousing and reporting solutions;
• SQL;
• Microsoft Power BI;
• databases and relational databases;
• data engineering;
• data lakes; 
• data pipelines;
• Informatica;
• Teradata;
• SAS;
• performance metrics
• analytical and problem-solving skills;
• effective communication skills;
• planning and organisational skills;
• service and stakeholder focus;
• conceptual thinking skills;
• innovation and creativity; and
• a drive for results.