Data Engineer (ETL/ELT)

Are you passionate about building scalable data pipelines and integrating enterprise systems? Do you enjoy working with modern Azure technologies and transforming data into valuable business insights? Would you like to contribute to an international analytics platform? Then we have an exciting opportunity for you!

The international IT company Intetics is looking for an experienced Data Engineer (ETL/ELT) to join our team.

The role involves designing, developing, and maintaining reliable data pipelines connecting enterprise systems, Azure Data Lake, Azure SQL, Microsoft Fabric, and Power BI. You will work on data integration, transformation, and optimization, ensuring high-quality, secure, and efficient data flows that support enterprise analytics and reporting.

• Design, develop, and maintain ETL/ELT pipelines for enterprise data integration.
• Build and optimize data pipelines using Azure Data Factory and/or Microsoft Fabric Data Factory.
• Integrate data from APIs, databases, and file-based sources.
• Implement data validation, quality controls, logging, and monitoring.
• Optimize pipeline performance and troubleshoot production issues.
• Support CI/CD processes and automated deployment of data pipelines.
• Collaborate 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.
• Strong troubleshooting and performance optimization skills.

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 enterprise data.