Senior data engineer

Cape Town, South Africa | Posted on 20/07/2026

The Data Engineer is responsible for designing, developing,and maintaining scalable data solutions that transform raw data into trusted,accessible, and actionable information. This role focuses on building andoptimizing data pipelines, data architectures, and data platforms that supportanalytics, business intelligence, machine learning, and operational reportingrequirements.

The successful candidate will work closely with Data Scientists, Analysts, Architects, and Business Stakeholders to design andimplement modern data engineering solutions that enable data-drivendecision-making across the organization.

Responsibilities Design, develop, and maintain scalable data pipelines andarchitectures to support business and analytical requirements.
Build and optimize databases, data warehouses, and datalakes for performance, reliability, and scalability.
Extract, transform, and load (ETL/ELT) data from a varietyof structured and unstructured sources.
Develop and implement automated processes for dataacquisition, integration, cleansing, transformation, and storage.
Define and implement data storage solutions based onbusiness and technical requirements.
Create and maintain physical and logical data models tosupport enterprise data initiatives.
Support data migrations across multiple databases, servers,and cloud platforms.
Ensure data quality, consistency, integrity, and governanceacross all data assets.
Collaborate with Data Scientists and Analytics teams tooperationalize machine learning models.
Develop data pipelines that support predictive analytics,artificial intelligence, and machine learning workloads.
Deploy machine learning models into production environments.
Build robust testing frameworks to validate datatransformations and model outputs.
Design and implement secure, scalable, and highly availabledata platforms.
Evaluate and recommend data solutions, technologies, andtools to address business requirements.
Develop databases optimized for analytics, reporting, andadvanced data processing.
Build and manage cloud-based data solutions utilizing moderncloud technologies.
Quality Assurance & Change Management Perform root-cause analysis and troubleshooting fordata-related issues.
Design and execute testing scenarios to validate dataquality and transformation accuracy.
Assess, document, and implement changes in accordance withchange management processes.
Ensure release processes, procedures, and documentation aremaintained and updated.
Support configuration management and release managementactivities.
Stakeholder Engagement Collaborate with business, analytics, and technical teams to improve data accessibility and usability.
Translate business requirements into technical datasolutions.
Provide recommendations regarding data architecture,integration, and optimization strategies.
Communicate complex technical concepts effectively to bothtechnical and non-technical stakeholders.
Skills Strong programming skills in Python, Bash, Shell Scripting, Perl
Advanced SQL development skills, including: SQL Server, My SQL
Relational database technologies: ETL/ELT processes, Datapipelines, Data warehouses, Data lakes
Experience working with large-scale structured andunstructured datasets.
Knowledge of data governance, data quality, and metadatamanagement practices.
Experience building and maintaining highly available andscalable systems.
Understanding of cloud platforms such as: Microsoft Azure Amazon Web Services (AWS), Google Cloud Platform (GCP), Hadoop, Cassandra, Storm, Similardistributed processing frameworks
Analytics & Reporting Working knowledge ofPower BI fordashboards, reports, and analytical solutions.
Understanding of Data visualization, Data virtualization, Augmentedanalytics, Business intelligence solutions.
Requirements 8+ years Proven experience in a Data Engineering role withina fast-paced technology environment.
Matric and a Bachelor's Degree in Computer Science, Information Technology
Cloud certifications (Azure, AWS, Google Cloud).
Professional data and analytics certifications.
Experience developing modern data and analytics platformsthat deliver actionable insights from large and complex datasets.
Strong hands-on experience with Python development.
Experience designing and supporting ETL/ELT frameworks anddata integration solutions.
Experience working with SQL Server, My SQL, and enterprisedatabase solutions.
Experience with cloud technologies, including Saa S, Paa S,and Iaa S environments.
Experience with automation, scripting, and data processorchestration.
Experience building secure, scalable, resilient, and highlyavailable data platforms.
Experience supporting machine learning and advancedanalytics initiatives.
Experience with big data technologies and distributedcomputing environments.