Intetics is hiring a Data Engineer to design, develop, and maintain scalable ETL/ELT data pipelines that connect enterprise systems to Azure data services for analytics. The role focuses on building pipelines using Azure Data Factory and Microsoft Fabric Data Factory, integrating APIs, databases, and file-based sources, and ensuring data quality, logging, and monitoring. Responsibilities include optimizing pipeline performance, implementing CI/CD processes for data pipelines, and collaborating with cross-functional teams to deliver reliable analytics solutions. Requirements include strong experience with Azure Data Factory and/or Microsoft Fabric Data Factory, Azure Data Lake and Azure SQL, advanced SQL, and proficiency in Python or another scripting language. Experience designing and maintaining production ETL/ELT pipelines, integrating APIs, databases, and file-based sources, and knowledge of incremental loading and data validation are essential. Nice to have: experience with Oracle or PeopleSoft, Spark, Databricks, or Microsoft Fabric Notebooks, and handling sensitive enterprise data such as HR, Finance, or Payroll.

Intetics is hiring a Data Engineer to design, develop, and maintain scalable ETL/ELT data pipelines that connect enterprise systems to Azure data services for analytics. The role focuses on building pipelines using Azure Data Factory and Microsoft Fabric Data Factory, integrating APIs, databases, and file-based sources, and ensuring data quality, logging, and monitoring. Responsibilities include optimizing pipeline performance, implementing CI/CD processes for data pipelines, and collaborating with cross-functional teams to deliver reliable analytics solutions. Requirements include strong experience with Azure Data Factory and/or Microsoft Fabric Data Factory, Azure Data Lake and Azure SQL, advanced SQL, and proficiency in Python or another scripting language. Experience designing and maintaining production ETL/ELT pipelines, integrating APIs, databases, and file-based sources, and knowledge of incremental loading and data validation are essential. Nice to have: experience with Oracle or PeopleSoft, Spark, Databricks, or Microsoft Fabric Notebooks, and handling sensitive enterprise data such as HR, Finance, or Payroll.