Data Engineer
RemoteUnited States
Job Summary
Design and maintain ETL pipelines to extract, transform, and load data from diverse source systems such as ERP, CRM, and work order management. Build scalable conceptual, logical, and physical data models to support business intelligence and operational reporting. Develop, maintain, and document standardized reporting solutions including paginated reports and interactive dashboards using Power BI. Monitor data quality, consistency, and pipeline performance while collaborating with stakeholders to translate requirements into reliable data solutions. Requires 5–8+ years of experience with SQL, DAX, and platforms like Microsoft Fabric or Azure Data Factory.
Required Qualifications
- 5–8+ years of experience in data engineering, business intelligence, data modeling, database design, or enterprise reporting
- Hands-on experience building, maintaining, and troubleshooting ETL or ELT pipelines using platforms such as Microsoft Fabric, Azure Data Factory, Databricks, or similar data engineering tools
- Experience developing Power BI reports and semantic models that support enterprise reporting, operational analytics, and recurring business review processes
- Demonstrated ability to work independently with business stakeholders, clarify requirements, manage assigned deliverables, and communicate progress, risks, and blockers clearly
- Strong hands-on technical proficiency with SQL, DAX, Power Query/M, and data modeling concepts, with the ability to write, troubleshoot, optimize, and document logic used in data pipelines, semantic models, reports, and dashboards
Desired Qualifications
- Experience developing operational service level agreement (SLA) reporting, KPI frameworks, and executive scorecards to track performance, identify trends, and support accountability across business operations
- Experience working in a source-controlled development environment using tools and practices such as Git, Azure DevOps, pull requests, branching strategies, deployment pipelines, or Microsoft Fabric development pipelines
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