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# Data Engineer

- **Company:** Preferred Credit
- **Location:** St. Cloud, MN, United States
- **Salary:** $82,000.0 - $102,500.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Azure, Cloud Database, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Systems, Relational Databases, Dimensional Modeling, Microsoft SQL Server, Operational Databases, Power BI, SQL Stored Procedures, Transact-SQL, Data Ingestion, Data Build Tool (dbt), Git, Build Management, Microsoft Fabric, Pyspark, Information Technology, Software Version Control, Data Pipelines
- **Published:** July 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=5191b8d6d8df363b

## About the Role

Are you looking for an opportunity to build modern data solutions, work with Microsoft Fabric, and make an impact with enterprise data? PCI is seeking an MS Fabric Data Engineer who is analytical, collaborative, and passionate about data engineering. You'll design and optimize data pipelines, build Medallion (Bronze/Silver/Gold) architecture, and support our migration from SQL Server to Microsoft Fabric.

This is an exciting opportunity to work with Microsoft Fabric, PySpark, dbt, and Power BI, solve complex data challenges, and grow your expertise in cloud data engineering and emerging technologies., Must-Have Qualifications:

 * BS in Computer Science or equivalent program or equivalent experience
 * 3-4 years of overall data engineering experience, with 1-2 years (minimum) of hands-on experience in Microsoft Fabric
 * Proficiency in PySpark and/or Python for data transformation and pipeline development
 * Strong T-SQL skills and understanding of relational database and dimensional modeling concepts

Nice to have but not Required!

 * Experience with DBT (Data Build Tool)
 * Exposure to MS Azure resources (e.g.-Functions, Eventhub etc.)
 * Experience with Power BI including semantic layer models
 * Familiarity with Azure DevOps, Git-based version control, and CI/CD pipelines

## Description

* Design and build ingestion pipelines from on-premises SQL Server and other source systems into Fabric using Mirroring, Copy Activity/Data Factory pipelines, and Fabric Notebooks.
 * Develop and maintain medallion architecture (Bronze, Silver, Gold) transformations using PySpark notebooks and dbt (Data Build Tool).
 * Implement schema evolution handling, watermark-based incremental loads, and data quality checks (row count drift, freshness, referential integrity) across pipeline layers.
 * Available for off-hours support as needed to address data pipeline failures or critical issues impacting production data systems.
 * Translate existing on-premises stored procedures and ETL logic into Fabric-native pipelines and dbt models as part of the SQL Server-to-Fabric migration.
 * Identify and remediate data pipeline failures, performance bottlenecks, and capacity constraints within Fabric capacity limits.


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