The Azure Data Engineer will be responsible for designing, building, optimizing, and maintaining data pipelines and data solutions within the Microsoft Azure ecosystem. The role requires strong experience in cloud-based data engineering, modern data architectures, and scalable data processing frameworks.

Key Responsibilities

• Design, develop, and maintain Azure-based data pipelines (batch and streaming).
  
• Implement ETL/ELT solutions using Azure Data Factory (ADF), Azure Databricks, Synapse Analytics, and related Azure services.
  
• Build and optimize data models, including Data Lakehouse architectures (Medallion, Delta Lake).
  
• Ensure data quality, integrity, and governance across all data processes.
  
• Collaborate with data scientists, analysts, and business teams to provide clean, reliable datasets.
  
• Perform pipeline monitoring, troubleshooting, performance optimization, and cost optimization.
  
• Develop CI/CD pipelines using Azure DevOps for data-related deployments.
  
• Implement security best practices, including RBAC, encryption, and data access governance.
  

Required Technical Skills

• Strong proficiency with Azure Data Factory (ADF), Azure Databricks (PySpark), and Azure Synapse Analytics.
  
• Expert knowledge of Python, SQL, and data transformation frameworks.
  
• Experience with Delta Lake, Spark, Data Lake Storage (ADLS), and distributed compute patterns.
  
• Familiarity with Data Vault, Dimensional Modelling, or Medallion architecture.
  
• Experience with cloud DevOps tools (Azure DevOps, GitHub Actions).
  
• Knowledge of streaming technologies (Kafka, Event Hubs) is an advantage.
  

Requirements

Qualifications & Certifications (Preferred)

• Azure certifications such as:
  • AZ‑900 Azure Fundamentals
    
  • DP‑203 Azure Data Engineer Associate
    
  • Databricks Data Engineer certifications
    
• Bachelor’s degree in Computer Science, Engineering, or related field.
  

Experience

• 5+ years of data engineering experience (Azure preferred).
  
• Proven experience building and supporting production-scale cloud data solutions.
  

Location & Working Model

• Location: Johannesburg (Hybrid working model)
  
• Ways of Working: Standard SAST business hours
  
• Candidate: Preferably a South African Citizen or Permanent Resident