Data Engineer

Littelfuse (NASDAQ: LFUS) is a diversified industrial technology manufacturing company shaping solutions for the safe and efficient transfer of electrical energy. Headquartered in Chicago, Illinois, USA, we serve customers across industrial, transportation, and electronics markets worldwide. With approximately 16,000 employees we design and manufacture innovative technologies that support electrification, energy efficiency, and advanced automation. Our global reach is matched by a culture that empowers innovation and long-term growth. Guided by our principles We Care, We Succeed With Our Customers, and We Own the Outcome, we work collaboratively, think boldly, and deliver solutions that move industries forward. We are seeking a Data Engineer with 2+ years of experience to design, develop, test, and support reliable data integration solutions. This role focuses on Azure Data Factory and SQL development for Master Data Management (MDM) initiatives, including data flows between SAP, BW, Data Hub, and Informatica. The successful candidate will work closely with technical and functional team members to deliver end-to-end data pipelines, database objects, testing, documentation, and deployment automation. About the job: Extract data from source systems, including SAP, BW, and Data Hub, and ensure data is available in the required structure and format. Develop, maintain, monitor, and test ETL/ELT processes and data pipelines using Azure Data Factory (ADF). Collaborate with cross-functional team members to implement and test the end-to-end MDM process, including Informatica egress files to Data Hub and Data Hub inputs to Informatica. Develop, optimize, and maintain SQL stored procedures in Azure to support MDM implementation and data processing requirements. Develop, maintain, and test data dictionary elements and database objects, including tables, views, schemas, and related metadata for the MDM project. Develop and maintain ADF-based data extraction and integration pipelines for the MDM project. Troubleshoot and debug ETL, pipeline, SQL, and data-quality issues; perform root-cause analysis and implement sustainable fixes. Create and maintain technical documentation, including data mappings, pipeline designs, support procedures, deployment notes, and operational runbooks. Participate in peer code reviews and consistently follow established coding, naming, security, and documentation standards. Implement and support CI/CD processes for data pipelines and database components across development, test, and production environments. Manage and version source code, deployment artifacts, and configuration changes using Git. About you: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent practical experience. 2+ years of hands-on experience in data engineering, data integration, ETL/ELT development, or a related role.