Azure Data Engineer (ID:3737)

As an Azure Data Engineer, you will: Design, build, and maintain scalable data pipelines and data storage solutions within the Microsoft Azure ecosystem. Develop and optimize ETL/ELT processes for ingesting, transforming, and processing large volumes of structured and unstructured data. Transform and cleanse raw data using PySpark and related technologies to ensure high data quality and optimal query performance. Work extensively with Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, and Azure SQL Database. Develop and optimize SQL queries, stored procedures, and data models for analytics and reporting needs. Implement and maintain CI/CD pipelines using Azure DevOps for automated deployments and streamlined development workflows. Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver scalable solutions. Monitor data pipelines, troubleshoot issues, and ensure reliability, scalability, and performance of data platforms. Follow best practices for data governance, security, and operational excellence. What You Bring to the Table: 6–8 years of experience in Data Engineering with strong expertise in Microsoft Azure data services. Hands-on experience with Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, and Azure SQL DB. Strong proficiency in Python, PySpark, and SQL for data transformation and engineering tasks. Experience in building scalable data pipelines and processing frameworks. Good understanding of ETL/ELT concepts, data modeling, and data warehousing principles. Hands-on experience with Azure DevOps and CI/CD pipeline implementation. Experience in performance optimization, troubleshooting, and data quality management. Strong analytical, problem-solving, and debugging skills. Ability to work independently in a dynamic and fast-paced environment. You Should Possess the Ability to: Design scalable and efficient cloud-based data engineering solutions. Process and optimize large datasets for analytics and business intelligence use cases. Collaborate effectively with cross-functional teams and stakeholders. Troubleshoot and resolve complex data pipeline and performance issues. Implement automation and DevOps best practices within data engineering workflows. Ensure data quality, reliability, and governance standards are maintained. Adapt quickly to evolving project requirements and technologies. What We Bring to the Table: Opportunity to work on enterprise-scale cloud data transformation initiatives. Exposure to modern Azure data engineering and analytics technologies. A collaborative and innovation-driven work environment. Opportunities to enhance expertise in cloud-native data platforms, big data processing, and DevOps practices. Let’s Connect Want to discuss this opportunity in more detail? Feel free to reach out. Recruiter: Hema Murali Phone: +31 20 369 0609 ; Extn :148 Email: hema.m@stafide.nl LinkedIn: https://www.linkedin.com/in/hema-murali-315999329/