The Senior Data Engineer is responsible for designing, developing, and maintaining advanced data architectures and pipelines that enable data-driven decision-making across the organization. This role involves end-to-end ownership of data solutions — from modelling and integration to optimization and governance. The incumbent ensures that data systems are scalable, reliable, and aligned with business and analytical requirements. As a senior member of the team, the role also includes mentoring mid-level engineers and contributing to best practice development within the data engineering discipline.
Key Responsibilities:
- Design logical and physical data models to support applications, analytics, and reporting needs; ensure models meet business requirements and are optimized for scalability and performance.
- Architect and implement robust data integration processes, including ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) workflows, to consolidate data from multiple internal and external sources.
- Design, build, and manage complex, high-performing data pipelines and architectures for batch and real-time data processing.
- Optimize data storage solutions, ensuring efficiency, reliability, and scalability within cloud and on-premise environments.
- Collaborate closely with data scientists, analysts, and business stakeholders to align data infrastructure with strategic and operational objectives.
- Implement and enforce data quality, validation, and governance standards to ensure accuracy and consistency of organizational data assets.
- Provide guidance and technical mentorship to junior and mid-level data engineers, promoting adherence to engineering best practices.
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 5 years’ experience in a Data Engineer or similar data-focused role.
- Proven expertise in data modelling, ETL/ELT pipeline development, and data integration.
- Hands-on experience with cloud-based data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
- Experience with big data frameworks (e.g., Spark, Hadoop) and modern orchestration tools (e.g., Airflow, Prefect).
Desired Skills:
- SQL
- Cloud
- Python
- Data Integration
- Data Modelling
- Data Security
- ETL
Desired Qualification Level:
- Diploma
About The Employer: