Lead Microsoft Data & AI Engineer (Hybrid)

Motion Recruitment

Minneapolis (MN)

Hybrid

USD 140,000 - 190,000

Full time

26 hours ago
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Job summary

Motion Recruitment seeks a Principal Microsoft Data & AI Engineer for a hybrid role across Minneapolis, MN, Irving, TX, or Charlotte, NC. The candidate will lead design and delivery of data platforms, leveraging SQL Server, Fabric, and AI-assisted workflows.

The role demands 7+ years in data/engineering, strong SQL, and hands-on experience with modern data platforms. Collaboration with business stakeholders is essential for delivering analytics-ready data assets.

Qualifications

  • 7+ years engineering experience or equivalent in data/analytics.
  • 7+ years in data engineering, analytics, or related.
  • Advanced hands-on SQL Server and complex SQL development.
  • Experience designing ETL/ELT pipelines.
  • Hands-on Microsoft Fabric or equivalent cloud data platform.
  • Strong data modeling knowledge (relational/dimensional/semantic).
  • Experience integrating enterprise data with diverse sources.

Responsibilities

  • Develop scalable data ingestion and integration pipelines using SQL Server and Fabric.
  • Design enterprise data models to support Power BI and AI workflows.
  • Write and optimize advanced SQL and data transformations.
  • Collaborate with stakeholders to translate requirements into data products.
  • Use AI tools to assist data analysis, SQL and code development, and documentation.
  • Ensure data governance, quality, and security across environments.

Skills

Communication skills
Independent work
AI experience
Problem solving

Tools

Microsoft SQL Server
Power BI
Excel
Azure Databricks
Microsoft Fabric
GitHub
Azure DevOps
CI/CD
Python/PySpark

Job description

Motion Recruitment seeks a Principal Microsoft Data & AI Engineer for a hybrid role across Minneapolis, MN, Irving, TX, or Charlotte, NC. The candidate will lead design and delivery of data platforms, leveraging SQL Server, Fabric, and AI-assisted workflows.

The role demands 7+ years in data/engineering, strong SQL, and hands-on experience with modern data platforms. Collaboration with business stakeholders is essential for delivering analytics-ready data assets.

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