Technology and Data - Engineer 5 - Contingent

Principal Microsoft Data & AI Engineer
Location: Minneapolis strongly preferred (2 engineers at that location); additional choices: Chandler, AZ , Irving, TX and Charlotte. Hybrid: 3 days onsite/ 2 days remote
 
Details:
Seeking a Principal Microsoft Data & AI Engineer who combines advanced SQL and Microsoft Fabric expertise with hands-on data engineering, data wrangling, analytical modeling, and practical experience using generative AI tools to accelerate data analysis and solution development.

Core platforms
Microsoft SQL Server, Microsoft Fabric, Azure, Power BI, Excel
Experience
7+ years in data engineering or a closely related discipline
Future platform
Databricks access expected in Q1 2027
Work style
Senior individual contributor; hands-on delivery and technical leadership

Primary Responsibilities
Design, build, test, deploy, and support scalable data ingestion, transformation, and integration solutions using Microsoft SQL Server and Microsoft Fabric.

• Develop reusable ETL and ELT processes that move data from authorized enterprise systems into governed analytical data stores and semantic models.
• Write and optimize advanced SQL, including complex queries, stored procedures, views, transformations, and performance-tuned processing routines.
• Design relational, dimensional, semantic, and analytical data models that support Power BI, Excel, human analysis, and approved AI-assisted analysis
• Design enterprise data models using repository-driven standards and Medallion methodology to deliver governed, high-quality, analytics-ready data assets.
• Integrate structured, semi-structured, and unstructured data from databases, Excel, CSV files, email-delivered files, APIs, exported reports, and authorized web-based sources.
• Create controlled, repeatable processes for nonstandard data sources with validation, reconciliation, traceability, and error handling.
• Profile data, identify quality issues, determine root causes, and implement remediation or monitoring controls.
• Build curated, analysis-ready datasets and semantic models for Power BI, Excel, analysts, and approved AI tools.
• Use approved generative AI tools to assist with data analysis, SQL and code development, documentation, testing, troubleshooting, and prompt-based workflows.
• Validate AI-generated SQL, code, calculations, summaries, and analytical conclusions before use.
• Translate business and analytical needs into clear data requirements, technical designs, and usable data products.
• Follow applicable data governance, privacy, information security, risk, and compliance requirements.
   

Skills Priority
1 Microsoft SQL Server and advanced SQL data engineering
2 Microsoft Fabric and modern data engineering patterns
3 Enterprise data modeling: repository-driven standards and Medallion methodology to create governed, high-quality, analytics-ready Fabric data assets and reusable models for hypothesis testing and analysis
4 ETL/ELT, data integration, data quality, metadata, and governed data product development
5 AI-assisted development and prompt engineering for data analysis
6 Advanced Microsoft Excel
7 Power BI
8 Azure data services
9 Power Apps / Power Automate
10 Databricks

Required Qualifications
• 7+ years of progressively responsible experience in data engineering, database engineering, analytics engineering, data integration, or a related discipline.
• Advanced hands-on Microsoft SQL Server and complex SQL development experience.
• Experience designing and delivering reusable ETL or ELT pipelines.
• Hands-on Microsoft Fabric experience or strong experience with a comparable modern cloud data platform.
• Strong knowledge of relational, dimensional, semantic, and analytical data modeling.
• Experience designing enterprise data models using repository-driven standards and Medallion methodology to create governed, high-quality, analytics-ready data assets.
• Experience integrating enterprise data with nonstandard sources such as Excel, files, APIs, email-delivered data, exported reports, or authorized website data.
• Demonstrated data profiling, validation, reconciliation, and data quality problem-solving experience.
• Advanced Excel skills, including Power Query, data models, PivotTables, advanced formulas, and external data connections.
• Experience preparing data for Power BI, Excel, human analysts, or AI-assisted analytical workflows.
• Working knowledge of source control, code review, testing, release management, and production support.
• Strong communication skills and the ability to explain technical designs, assumptions, limitations, and findings to nontechnical stakeholders.
• Ability to work independently and manage ambiguity in a complex, regulated enterprise environment.

AI Experience
Candidates should have practical, work-related experience with one or more AI-assisted engineering or productivity tools, such as Microsoft 365 Copilot, GitHub Copilot, Claude Code, Microsoft Cowork, Devin,
Visual Studio Code with approved AI extensions, or other enterprise-approved LLM tools.
• Developing and refining prompts for data discovery, analysis, SQL generation, testing, documentation, and interpretation of results.
• Providing schema context, definitions, examples, constraints, and expected output formats within prompts.
• Validating AI-generated SQL, calculations, code, summaries, and analytical conclusions.
• Recognizing hallucinations, unsupported conclusions, incorrect assumptions, and data leakage risk.
• Creating repeatable prompt templates or AI-assisted workflows that improve analyst productivity.

Preferred Qualifications
• Microsoft Fabric Lakehouse, Warehouse, Data Factory, Dataflows Gen2, notebooks, or semantic model experience.
• Azure SQL, Azure Data Lake Storage, Azure Data Factory, or related Azure data services.
• Python, PySpark, PowerShell, or another data transformation and automation language.
• Power BI experience, including semantic models, DAX, Power Query, performance optimization, and executive reporting.
• Power Apps or Power Automate experience.
• Databricks, Delta Lake, Spark, medallion architecture, or comparable lakehouse experience.
• Experience supporting both traditional business intelligence and AI-based analysis.
• Experience with APIs, JSON, XML, HTML parsing, browser automation, or approved web data extraction.
• Experience working with confidential or sensitive data in a regulated environment.
• GitHub, Azure DevOps, ServiceNow, CI/CD, or automated testing experience.