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# BI Engineer

- **Company:** Miracle Software Systems, Inc.
- **Location:** Troy, MI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Adaptable Database Systems, Analysis of Variance (ANOVA), Data Architecture, Data Warehousing, Database Queries, Performance Tuning, Power BI, Reverse Engineering, Data Layers, Microsoft Fabric, Star Schema, Custom Reports
- **Published:** August 5, 2026
- **Apply:** https://www.dice.com/job-detail/d7d36631-137b-4976-8c1e-789cba001a35

## About the Role

* Advanced Power BI development experience, including enterprise-grade report design, complex data modeling, performance optimization, and reusable reporting patterns.
 * Strong semantic model design experience, including star schema modeling, fact/dimension design, relationships, hierarchies, calculation groups, and governed business metrics.
 * Advanced DAX expertise for complex measures, calculated tables, time intelligence, KPI calculations, variance analysis, and performance-tuned reporting logic.
 * Hands-on experience with Microsoft Fabric, including Lakehouse/Warehouse concepts, semantic models, Power BI integration, dataflows/pipelines, and medallion-style data architecture.
 * Strong SQL skills with the ability to analyze, reverse-engineer, and modernize reporting logic from legacy data warehouse environments.
 * Experience migrating reports from legacy BI platforms to Power BI, including report rationalization, metric validation, data reconciliation, and user acceptance support.
 * Ability to define and support a KPI Registry, including business definitions, calculation logic, ownership, lineage, certification, and governance.
 * Strong analytical and client-facing skills, with the ability to work directly with business users, understand legacy processes, and translate requirements into scalable data models, semantic layers, and Power BI solutions.
 * Understanding of AI-ready data foundations, including governed datasets, trusted metrics, metadata, lineage, and reusable semantic models for future AI enablement.



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