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# Azure Data Engineer Microsoft Fabric & Power BI

- **Company:** McKinsol Consulting Inc
- **Location:** Warrenville, IL, United States
- **Contract:** Permanent contract
- **Skills:** Microsoft Online Services, Continuous Delivery, Extract Transform Load (ETL), DevOps, Dimensional Modeling, Python (Programming Language), Power BI, Azure Data Lake, SQL Databases, Transact-SQL, Microsoft Fabric, Data Lakes, Pyspark, Data Analytics, Star Schema, Data Pipelines, Databricks
- **Published:** July 30, 2026
- **Apply:** https://www.dice.com/job-detail/d09dfd59-251a-41ac-a481-48a6cf8ef45e

## About the Role

Python, PySpark, SQL (T-SQL), DAX

Compute & Storage

Microsoft Fabric (OneLake, Data Factory, Lakehouse), Azure Databricks, ADLS Gen2, Delta Lake

Data Modeling

Kimball Dimensional Modeling, Star Schema, Fact Tables, Dimension Tables, Medallion Architecture

BI & Analytics

Power BI, Semantic Models (Direct Lake, Import, DirectQuery), DAX Measures

DevOps & Practices

## Description

This is a standard enterprise-grade Data & Analytics Engineer role with a heavy focus on the Microsoft Cloud Stack.

The ideal candidate manages the entire data lifecycle from raw ingestion to end-user semantic modeling in Power BI.

Core Technical Pillars:

Medallion Architecture & Storage: Architecting Bronze (raw), Silver (cleansed/conformed), and Gold (aggregated star schema) layers using Delta Lake on Microsoft Fabric (OneLake) or Azure Databricks (ADLS Gen2).

Pipeline Development: Building ETL/ELT pipelines with PySpark, SQL, and Microsoft Fabric Data Factory / Notebooks.

Hybrid BI Capabilities: Developing enterprise-grade Power BI semantic models (leveraging Direct Lake mode) and writing complex DAX measures.

DevOps & Governance: Implementing CI/CD pipelines for data workloads and Power BI assets, setting engineering standards, and writing technical documentation.


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