The Data Engineer is responsible for designing, developing, and maintaining robust data architectures and pipelines that enable data-driven insights and support business intelligence, analytics, and machine learning initiatives. This role involves end-to-end ownership of data modelling, integration, and security to ensure that enterprise data systems are scalable, high-performing, and compliant with data governance and regulatory standards. The incumbent plays a key role in ensuring the organization’s data ecosystem remains efficient, secure, and aligned with evolving business and technology requirements.
Key Responsibilities:
- Design logical and physical data models to meet application and analytical requirements, ensuring that models are optimized for performance, scalability, and alignment with business needs.
- Develop and implement efficient data integration workflows using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes to ensure seamless consolidation of data from various internal and external sources.
- Build and maintain scalable, high-performance data architectures that support both batch and real-time data processing.
- Ensure data solutions comply with relevant data privacy, governance, and security regulations. Implement robust data security measures, including encryption, role-based access control, and activity monitoring.
- Optimize data storage and retrieval mechanisms for performance, reliability, and scalability across cloud and on-premise environments.
- Work closely with data scientists, analysts, and business stakeholders to understand data requirements and translate them into sustainable data solutions.
- Stay current with emerging trends, technologies, and best practices in data engineering, applying innovative solutions to enhance data systems and workflows.
Requirements
- NQF Level 6 or higher tertiary qualification in an Information and Communication Technology (ICT) field (e.g., Computer Science, Information Systems, Data Engineering, or related discipline).
Cloud certification (AWS, Azure, or GCP) preferred. - Minimum of 6 years’ experience in a Data Engineer or related technical data role.
- Proven experience in data modeling, ETL/ELT development, and data integration.
- Experience implementing data security, compliance, and governance frameworks.
- Hands-on experience with cloud-based data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
Desired Skills:
- SQL
- Cloud
- Python
- Data Integration
- Data Modelling
- Data Security
- ETL
Desired Qualification Level:
- Diploma
About The Employer: