Cloud Data Engineers (OVA5720)
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Cloud Data Engineers (OVA5720)
Location
Johannesburg, South Africa
Experience
Mid
Posted
Jul 18, 2026
Apply by
July 24, 2026
Applicants
0
Early applicantEasy applyContractHybrid
Job Description
We're Hiring: Cloud Data Engineer (Azure) | Banking Industry
12 months contract-Hybrid
Are you passionate about building modern cloud-based data platforms that power advanced analytics, AI, and business intelligence?
Our client, a leading financial institution, is looking for an experienced Cloud Data Engineer to join their growing data team.
About the Role
The Cloud Data Engineer is responsible for preparing enterprise-grade data products and driving technical thought leadership to support advanced analytics initiatives. This role involves designing, developing, and maintaining scalable data solutions on Microsoft Azure, ensuring the delivery of clean, reliable, and fit-for-purpose data across the organisation.
You will build robust data pipelines, integrate APIs, and leverage Azure services to enable advanced analytics, machine learning, and business intelligence capabilities while supporting the bank's data-driven strategy.
Key Responsibilities
Design, build, and maintain scalable data pipelines using Azure, Microsoft Fabric, Databricks, Ab Initio, Python, PySpark, and Spark
Develop and optimize data ingestion, transformation, and delivery processes across Data Warehouses and Data Lakes
Implement DataOps practices, workflow orchestration, automated testing, and CI/CD pipelines
Integrate APIs and support real-time data consumption for business applications
Enable low-latency and streaming data solutions using Kafka, Azure Event Hub, and related technologies
Ensure data quality, governance, lineage, metadata management, and regulatory compliance (POPIA)
Manage and optimize cloud and hybrid data platforms for performance, scalability, and reliability
Collaborate with Data Scientists, Analysts, Architects, and Business Stakeholders to deliver innovative data solutions
Drive continuous improvement, innovation, and technical best practices across the data engineering function
Requirements
Undergraduate Degree
Experience in Data Engineering, Data Platforms, or Business Intelligence environments
Strong expertise in Microsoft Azure, Azure Data Factory, Microsoft Fabric, Databricks, Python, and PySpark
Experience with DataOps, Infrastructure as Code, workflow orchestration, and CI/CD practices Knowledge of data governance, data quality, metadata management, and enterprise data architectures
Experience with API integration and real-time data processing technologies
Key Responsibilities
- Design, build, and maintain scalable data pipelines using Azure, Microsoft Fabric, Databricks, Ab Initio, Python, PySpark, and Spark
- Develop and optimize data ingestion, transformation, and delivery processes across Data Warehouses and Data Lakes
- Implement DataOps practices, workflow orchestration, automated testing, and CI/CD pipelines
- Integrate APIs and support real-time data consumption for business applications
- Enable low-latency and streaming data solutions using Kafka, Azure Event Hub, and related technologies
- Ensure data quality, governance, lineage, metadata management, and regulatory compliance (POPIA)
- Manage and optimize cloud and hybrid data platforms for performance, scalability, and reliability
- Collaborate with Data Scientists, Analysts, Architects, and Business Stakeholders to deliver innovative data solutions
- Drive continuous improvement, innovation, and technical best practices across the data engineering function
Requirements
- Undergraduate Degree
Skills Required
Microsoft AzureAzure Data FactoryMicrosoft FabricDatabricksPythonPySparkSparkDataOpsInfrastructure as CodeWorkflow orchestrationCI/CDAPI integrationKafkaAzure Event HubData WarehousesData LakesData GovernanceMetadata ManagementPOPIACollaborationTechnical thought leadership
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