Remote Data Engineer (ETL/ELT) role at Intetics to design, build, and maintain scalable data pipelines that connect enterprise systems with Azure Data Lake, Azure SQL, Microsoft Fabric, and Power BI. You will work on data integration, transformation, and optimization to support enterprise analytics and reporting, ensuring high-quality, secure, and efficient data flows. Responsibilities include designing and maintaining production ETL/ELT pipelines for enterprise data integration; building and optimizing pipelines with Azure Data Factory and/or Microsoft Fabric Data Factory; integrating data from APIs, databases, and file-based sources; implementing data validation, logging, and monitoring; troubleshooting production issues; supporting CI/CD for data pipelines; and collaborating with cross-functional teams to deliver reliable data solutions. Requirements: strong experience with Azure Data Factory and/or Microsoft Fabric Data Factory; hands-on experience with Azure Data Lake and Azure SQL; advanced SQL skills; proficiency in Python or another scripting language; experience designing and maintaining production ETL/ELT pipelines; experience integrating APIs, databases, and file-based data sources; knowledge of incremental loading, historical data processing, and data validation; experience implementing logging, monitoring, and error handling; experience with CI/CD for data pipelines. Nice to Have: experience integrating Oracle or PeopleSoft systems; experience with Spark, Databricks, or Microsoft Fabric Notebooks; experience working with HR, Finance, Payroll, or other sensitive

Remote Data Engineer (ETL/ELT) role at Intetics to design, build, and maintain scalable data pipelines that connect enterprise systems with Azure Data Lake, Azure SQL, Microsoft Fabric, and Power BI. You will work on data integration, transformation, and optimization to support enterprise analytics and reporting, ensuring high-quality, secure, and efficient data flows. Responsibilities include designing and maintaining production ETL/ELT pipelines for enterprise data integration; building and optimizing pipelines with Azure Data Factory and/or Microsoft Fabric Data Factory; integrating data from APIs, databases, and file-based sources; implementing data validation, logging, and monitoring; troubleshooting production issues; supporting CI/CD for data pipelines; and collaborating with cross-functional teams to deliver reliable data solutions. Requirements: strong experience with Azure Data Factory and/or Microsoft Fabric Data Factory; hands-on experience with Azure Data Lake and Azure SQL; advanced SQL skills; proficiency in Python or another scripting language; experience designing and maintaining production ETL/ELT pipelines; experience integrating APIs, databases, and file-based data sources; knowledge of incremental loading, historical data processing, and data validation; experience implementing logging, monitoring, and error handling; experience with CI/CD for data pipelines. Nice to Have: experience integrating Oracle or PeopleSoft systems; experience with Spark, Databricks, or Microsoft Fabric Notebooks; experience working with HR, Finance, Payroll, or other sensitive