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# Data Engineering Manager

- **Company:** Macro.CCS, Inc
- **Location:** Seattle, WA, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Microsoft Azure, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Systems, Microsoft SQL Server, Power BI, Cloud Services, Azure Data Factory, Apache Spark, Microsoft Fabric, Data Lakes, Star Schema, Data Management, Data Pipelines, Databricks
- **Published:** July 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b65b9d29cffa52b5

## About the Role

* 8+ years in IT and data systems, with at least 5 focused on data engineering or building data platforms
 * A track record of leading and mentoring engineering teams working on cloud data platforms
 * Hands-on depth with Azure data tools like Synapse, Data Factory, and Data Lake Storage (bonus points for Microsoft Fabric)
 * Comfort with data modeling approaches like star schema, medallion architecture, and semantic models
 * Real experience building ETL/ELT pipelines and transforming data at enterprise scale
 * Some exposure to data governance tooling (Microsoft Purview) and Master Data Management concepts
 * Enough Power BI know-how to understand how your work feeds reporting and semantic models
 * Familiarity with Agile ways of working, plus strong communication and prioritization chops
 * Nice-to-haves: Databricks, Delta Lake, or Spark; Azure DevOps and SQL Server; a background in ML or advanced analytics
 * Willingness to travel regionally, be on call as needed, and a bachelor's in a technical field (or equivalent experience), * Bachelor's (Preferred)

Experience:

 * data systems: 8 years (Required)
 * data engineering or building data platforms: 5 years (Required)

## Description

This person will help guide the shift from Synapse to Microsoft Fabric, keeping pipelines and data models solid, and make sure everything is fast, secure, and reliable enough to power analytics and AI work. Role also involves day-to-day management of a team of data engineers - coaching, setting the technical direction, and championing a data platform vision that folks across IT, analytics, and the business can rally behind.


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