Senior Azure Data Engineer

Role Overview: As a Senior Azure Data Engineer specializing in Databricks, PySpark, Microsoft Fabric, and Azure Data Services, you will be responsible for designing, developing, and optimizing enterprise-scale data platforms. Your role will involve creating end-to-end data pipelines, integrating SAP data sources, implementing scalable data architectures, and enabling analytics through Microsoft Fabric. Key Responsibilities: - Design and develop scalable ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric. - Build and optimize data ingestion, transformation, and orchestration workflows using Databricks and PySpark. - Integrate enterprise data sources, including SAP systems, into Microsoft Fabric Lakehouse and Data Warehouse. - Develop and maintain data models for analytics and reporting requirements. - Implement monitoring, logging, data quality, and performance optimization frameworks. - Collaborate with business, analytics, and application teams to deliver reliable data solutions. - Support CI/CD, deployment automation, and data governance initiatives. Qualifications Required: - 4+ years of hands-on Azure Data Engineering experience. - Strong expertise in Azure Databricks, PySpark, and Python. - Experience with Azure Data Factory and Azure Data Lake Storage (ADLS Gen2). - Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines). - Strong SQL and data modeling skills. Additional Details: - Preferred Skills: - SAP data integration and understanding of SAP data structures. - Unity Catalog implementation and governance experience. - Delta Lake and Spark-based processing. - Azure DevOps and CI/CD pipelines. - Power BI integration and reporting support. - Experience with real-time or near real-time data ingestion. - Knowledge of data governance and security best practices. - Azure DP-203 and/or Microsoft Fabric certification. - Education: Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or related field. Role Overview: As a Senior Azure Data Engineer specializing in Databricks, PySpark, Microsoft Fabric, and Azure Data Services, you will be responsible for designing, developing, and optimizing enterprise-scale data platforms. Your role will involve creating end-to-end data pipelines, integrating SAP data sources, implementing scalable data architectures, and enabling analytics through Microsoft Fabric. Key Responsibilities: - Design and develop scalable ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric. - Build and optimize data ingestion, transformation, and orchestration workflows using Databricks and PySpark. - Integrate enterprise data sources, including SAP systems, into Microsoft Fabric Lakehouse and Data Warehouse. - Develop and maintain data models for analytics and reporting requirements. - Implement monitoring, logging, data quality, and performance optimization frameworks. - Collaborate with business, analytics, and application teams to deliver reliable data solutions. - Support CI/CD, deployment automation, and data governance initiatives. Qualifications Required: - 4+ years of hands-on Azure Data Engineering experience. - Strong expertise in Azure Databricks, PySpark, and Python. - Experience with Azure Data Factory and Azure Data Lake Storage (ADLS Gen2). - Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Pipelines). - Strong SQL and data modeling skills. Additional Details: - Preferred Skills: - SAP data integration and understanding of SAP data structures. - Unity Catalog implementation and governance experience. - Delta Lake and Spark-based processing. - Azure DevOps and CI/CD pipelines. - Power BI integration and reporting support. - Experience with real-time or near real-time data ingestion. - Knowledge of data governance and security best practices. - Azure DP-203 and/or Microsoft Fabric certification. - Education: Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or related field.