Azure Data Engineer

We seek an experienced Azure Data Engineer to design, build, and implement robust cloud-based data infrastructure and services. The candidate should have hands-on expertise with Azure Data & Analytics PaaS services, scalable data pipelines, and end-to-end data integration. You will collaborate with cross-functional teams to turn business use cases into technical solutions, enabling data-driven decision-making.
Key Responsibilities:

• Data Engineering & Integration:
  

  • Design, build, and implement cloud infrastructure and data solutions using Azure services.
    

  • Develop scalable and secure data pipelines for data integration and processing using Azure Data Factory, Azure Databricks, and Azure SQL Warehouse .
    

  • Build and maintain data models and schemas in Azure SQL Warehouse to support analytics and reporting.
    

  • Data Exposure & End-User Solutions:
    

    • Expose data to end-users via tools like Power BI and Azure API Apps .
      

    • Implement data storage solutions using Azure services such as storage accounts and Azure Data Lake.
      

    • Data Profiling & Design:
      

      • Conduct data profiling, cataloguing, and mapping for technical design and construction of data flows.
        

        
        

        • Turn business use cases and requirements into technical solutions that align with organizational goals.
          

          • CI/CD & Automation:
            

            • Design and optimize CI/CD pipelines using tools like GitHub and Azure DevOps to streamline data workflows.
              

            • Automate data pipelines for efficient ingestion, processing, and distribution.
              

            • Data Security & Governance:
              

              • Implement robust data security measures , including encryption, access controls, and auditing, to protect sensitive information.
                

              • Ensure compliance with data governance principles and regulations, including metadata management and data lineage.
                

              • Collaboration & Documentation:
                

                • Work closely with data scientists, analysts, and stakeholders to understand data requirements and deliver tailored solutions.
                  

                • Document processes, pipelines, and system architecture to support knowledge sharing and maintainability.
                  

                  
                  
                  Requirements Required Skills & Qualifications:
                  

                  • Proficiency in Azure Data & Analytics PaaS services :
                    

                    • Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure Analysis Services, etc.
                      

                    • Experience designing and implementing scalable and secure data storage solutions on Azure, including Azure SQL Warehouse .
                      

                    • Hands-on expertise in building and maintaining data pipelines for integration and processing using Azure services .
                      

                    • Proficiency in SQL, T-SQL, and Spark SQL for data analysis and transformation.
                      

                    • Strong knowledge of CI/CD pipelines and automation using tools like Azure DevOps and GitHub.
                      

                    • Experience in data modelling, cataloguing, and technical mapping for efficient data flow design.
                      

                      
                      

                      • Exposure to data visualization tools like Power BI and end-user data integration via Azure API Apps .
                        

                      • Strong understanding of cloud security practices using Azure Key Vault and RBAC .
                        

                      • Exposure to advanced analytics tools such as Azure Machine Learning and Azure Stream Analytics .
                        

                      • Experience with agile methodologies and prototyping.