Principal Microsoft Data & AI Engineer - Hybrid

Genesis10•Minneapolis, MN

11d•Hybrid

About The Position

Genesis10 is currently seeking a Principal Microsoft Data & AI Engineer - Hybrid position with a Global Financial Institution. This is an 18+ month contract opportunity. This is a senior, hands-on data engineering role to design and deliver trusted data products for workforce analytics, operational reporting, executive decision-making, and AI-assisted analysis. The ideal candidate will take ownership of complex data problems from initial source assessment through ingestion, transformation, data quality validation, modeling, documentation, and delivery of analysis-ready data products. The environment is primarily within the Microsoft ecosystem, utilizing SQL Server, Microsoft Fabric, Azure, Power BI, and Excel.

Requirements

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
Practical, work-related experience with one or more AI-assisted engineering or productivity tools (e.g., Microsoft 365 Copilot, GitHub Copilot)
Experience developing and refining prompts for data discovery, analysis, SQL generation, testing, documentation, and interpretation of results
Ability to validate AI-generated SQL, calculations, code, and recognize hallucinations or unsupported conclusions
Strong communication skills and the ability to explain technical designs to nontechnical stakeholders
Ability to work independently and manage ambiguity in a complex, regulated enterprise environment

Nice To Haves

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 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

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

Benefits

Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years.
The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years.
Access to an experienced, caring recruiting team (more than 7 years of experience, on average.)
Behavioral Health Platform
Medical, Dental, Vision
Health Savings Account
Voluntary Hospital Indemnity (Critical Illness & Accident)
Voluntary Term Life Insurance
401K
Sick Pay (for applicable states/municipalities)
Commuter Benefits (Dallas, NYC, SF, and Illinois)