Data Engineer

About the role

Capitec is hiring a Data Engineer. Python | SQL | AWS | Redshift | Data Lakes | Data Warehouses | ETL/ELT | Batch Processing | Streaming / Real-time Pipelines | Git | CI/CD | Terraform / Infrastructure as Code | Data Modelling | Data Quality | Data Governance | Workflow Orchestration | Power BI / Microsoft Data Stack exposure | AI tooling and automation We're looking to connect with Data Engineers across a range of experience levels, from professionals building their foundational skills through to highly experienced engineers leading complex data initiatives. You may be a strong fit if you have experience with SQL, Python, data warehousing, cloud platforms (AWS, Azure or GCP), ETL/ELT pipelines, data modelling, and Agile delivery practices. Depending on your level of experience, you may be contributing to data pipeline development, system analysis and solution design, independently building and maintaining cloud-native data solutions, or taking technical ownership of large-scale platforms, architecture, performance optimisation, governance, CI/CD, infrastructure-as-code, and engineering standards. We welcome individuals who are passionate about data, enjoy solving complex problems, collaborate effectively with stakeholders, and are looking to grow their expertise in areas such as cloud engineering, data architecture, AI-enabled engineering, platform design, and technical leadership.

Requirements

• Education (Minimum)
• Bachelor's Degree in Information Technology
• Education (Ideal or Preferred)
• Honours Degree in Information Technology - Computer Science or Information Technology
• Knowledge and Experience
• Knowledge
• Expert level SQL knowledge with query optimisation and tuning and indexing strategies.
• Architecture design for batch and streaming systems
• Deep knowledge of multiple programming languages and implementation of advanced algorithms for data processing.
• Design enterprise wide real-time / batch data integration architectures.
• Advanced knowledge of one cloud platforms data services.
• Design and implementation of data lake, data warehouse or other patterns.
• Implementation of enterprise-wide data governance frameworks with automated quality and monitoring.
• Ability to performance optimize across heterogeneous systems.
• Design of multi-environment GitOps strategies, that includes feature flags and other advanced techniques.
• Design & Implementation of containerized data solutions and infrastructure using infrastructure as code
• Design and configuration enterprise workflow orchestration tools and pipelines
• Experience
• Length of experience required is conditional on the qualifications obtained but must include:
• Proven track record of leading large-scale data engineering projects and driving business impact through data solutions
• Experience with advanced data engineering tools and software (e.g., SQL, Python, Java, Apache Spark, Hadoop).
• Experience with machine learning algorithms and their application in predictive analytics
• Experience in designing and implementing complex data architecture and infrastructure.
• With cloud computing platforms (e.g., AWS, Azure, Google Cloud) and their data services 2.
• Experience in aligning data engineering projects with business strategy and goals.
• Experience in providing data-driven recommendations to senior management and influencing decision-making.
• Experience in leading and mentoring less experienced engineers and data teams.
• In people development, sharing and training.
• Skills
• Analytical Skills
• Communications Skills
• Computer Literacy (MS Word, MS Excel, MS Outlook)
• Interpersonal & Relationship management Skills
• Problem solving skills