Data Engineer

Exponential Technology Group (XTG) is a specialist in the electronic component distribution and design engineering services industries. The Data Engineer role is responsible for designing, building, and maintaining scalable data pipelines and integrations that support enterprise reporting and analytics, while contributing to the modernization of XTG’s data platform.

Responsibilities:

• Design, develop, test, and maintain data pipelines, dataflows, notebooks, and integration processes across enterprise systems
• Build and support data ingestion frameworks using Microsoft Fabric, Lakehouse/Warehouse architecture, SQL, and cloud-based data engineering patterns
• Develop and maintain Bronze, Silver, and Gold layer data structures to support reporting, analytics, and downstream business processes
• Create scalable ETL/ELT processes to extract, cleanse, transform, and load data from ERP, CRM, operational, and third-party systems
• Partner with business stakeholders, analysts, and application teams to clarify data requirements and translate them into technical solutions
• Support data migration and integration efforts related to Dynamics 365 and other enterprise platform initiatives
• Develop and maintain SQL queries, stored procedures, views, data models, and transformation logic
• Implement data quality checks, validation rules, logging, error handling, and monitoring within data pipelines
• Troubleshoot and resolve issues related to data accuracy, pipeline failures, source system changes, performance, and integration errors
• Contribute to data architecture, governance, naming standards, documentation, and reusable engineering patterns
• Use Azure DevOps, Git, branching strategies, and CI/CD practices to manage source control and deployment of data engineering assets
• Collaborate with reporting and analytics teams to support Power BI semantic models, dashboards, and enterprise reporting needs
• Provide guidance and support to junior team members, analysts, or business users as needed
• Continuously expand technical knowledge across Microsoft Fabric, Azure, Power BI, Dynamics 365, and modern data engineering practices
• Additional duties as assigned

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field, or equivalent professional experience
• 4+ years of professional experience in data engineering, business intelligence, analytics engineering, or enterprise data integration
• Experience building and maintaining data pipelines, ETL/ELT processes, data warehouses, lakehouses, or cloud-based analytics platforms
• Strong SQL development skills, including query optimization, joins, aggregations, views, stored procedures, and data validation logic
• Hands-on experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, or similar cloud data platforms
• Ability to work independently on complex technical tasks while collaborating with business and technical stakeholders
• Strong documentation skills, including technical designs, data mappings, source-to-target logic, and operational procedures
• This position requires use of information or access to hardware which is subject to the International Traffic in Arms Regulations (ITAR). To perform the position, you must be a U.S. Person as defined by ITAR. ITAR defines a U.S. person as a U.S. Citizen, U.S. Permanent Resident (i.e. ‘Green Card Holder'), Political Asylee, or Refugee
• Visa sponsorship is not available for this role. Only candidates authorized to work in the United States will be considered
• Experience working with enterprise systems such as ERP, CRM, financial, operational, or supply chain platforms
• Experience supporting data migration, system integration, or enterprise reporting initiatives
• Working knowledge of Power BI, semantic models, data modeling, and reporting data structures
• Exposure to or interest in AI-assisted development, automation, metadata-driven frameworks, or agentic AI tooling
• Microsoft certifications related to Fabric, Azure Data Engineering, Power BI, or Data Fundamentals preferred but not required