Senior Data Engineer

Cape Town - South Africa

Monthly Salary: Not Disclosed

Experience Required: 5years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

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).

Required Skills:

SQL Cloud Python Data Integration Data Modelling Data Security ETL

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).

Required Skills:

SQL Cloud Python Data Integration Data Modelling Data Security ETL