| We are looking for an experienced Azure Data Engineer to design, build, and maintain scalable data pipelines and cloud-based analytics solutions on the Microsoft Azure platform. The ideal candidate will have hands-on experience with Azure Data Factory, Data Lake, Synapse, Databricks, and SQL, and will collaborate with data architects and business teams to enable data-driven decision-making. Key Skills: Azure Data Factory (ADF), Azure Data Lake, Synapse Analytics, Databricks, SQL, Python, PySpark, ETL Development, Power BI (Basic), Data Modeling, CI/CD, Azure DevOps, JSON, Data Governance, Azure Storage, Performance Optimization. Roles and Responsibilities: Design and develop scalable ETL pipelines and data workflows using ADF and Databricks. Build and maintain data storage solutions on Azure Data Lake and Synapse. Optimize data ingestion, transformation, and loading processes. Collaborate with analysts and data scientists to enable business insights. Implement data validation, monitoring, and logging frameworks for reliability. Manage version control and deployment using Azure DevOps CI/CD pipelines. Ensure data security, compliance, and governance within Azure environments. Troubleshoot and resolve performance issues in data processing pipelines. Technical Environment: Languages: SQL, Python, PySpark Tools: Azure Data Factory, Synapse, Databricks, Power BI Storage: Azure Data Lake, Blob Storage DevOps: Git, Azure DevOps Concepts: Data Warehousing, ETL, Data Governance, Security Qualifications: Bachelor's degree in Computer Science, Information Technology, or related field. 5+ years of experience in data engineering with at least 2+ years in Azure ecosystem. Strong SQL and Python programming skills. Excellent understanding of cloud-based data architecture and pipeline optimization. Nice to Have: Microsoft Certified: Azure Data Engineer Associate. Experience with real-time data streaming (Event Hub, Kafka). Knowledge of Power BI dashboard integration and automation. | 
