Azure Data Engineer

Azure Data Engineer

Build enterprise-scale data pipelines and modern cloud data solutions in a high-growth environment.

Johannesburg (Bryanston)
· Hybrid Work
· R700 000 to R CTC per annum

Our client specialises in delivering advanced, cloud-based data solutions for large enterprises across diverse sectors. They leverage the Microsoft data ecosystem to build high-performance architectures that enable analytics, machine learning, and data-driven decision-making. The environment is fast-paced, innovative, and focused on technical excellence and continuous learning.

This role focuses on designing, developing, and maintaining data pipelines and cloud-based data solutions using Azure Data Factory or Azure Data Fabric. You will work across analytics, engineering and architecture teams to ensure data is accessible, reliable and optimised for use across the business.

• Build and maintain data ingestion, transformation and orchestration pipelines using Azure Data Factory or Azure Fabric.
• Design and implement data structures across Lakehouse, Data Lake and Warehouse environments.
• Optimise dataflows to ensure performance, scalability and reliability.
• Develop ETL/ELT processes aligned to architectural and business requirements.
• Integrate structured and unstructured data sources into unified, consumable models.
• Apply data governance, security and quality standards across all pipelines and datasets.
• Collaborate with analytics, BI, ML and engineering teams on cross-functional data initiatives.
• Troubleshoot pipeline issues and implement monitoring, alerting and automation.

• 3+ years of experience as a Data Engineer working with Azure Data Factory and/or Azure Data Fabric.
• Strong experience building data ingestion, transformation and orchestration pipelines.
• Skilled in designing Lakehouse, Data Lake and Data Warehouse solutions.
• Able to optimise and troubleshoot complex dataflows and integrations.
• Familiar with data governance, security principles and quality frameworks.
• Comfortable working with both structured and unstructured datasets.
• Proactive, analytical and detail-oriented with strong problem-solving skills.