Principal Microsoft Data & AI Engineer

Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Integrate structured, semi-structured, and unstructured data from databases, Excel, CSV files, email-delivered files, APIs, exported reports, and authorized web-based sources.

Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Principal Microsoft Data & AI Engineer in Minneapolis, MN, Irving, TX, or Charlotte NC. (Hybrid).

Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.

Contract Duration: 18 Months

Required Skills & Experience

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
• 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.

Desired Skills & Experience

• Business Intelligence & Reporting
• Advanced MS Excel
• Artificial Intelligence (AI)
• Azure Databricks
• Data Modeling
• Microsoft Fabric Components
• Power bi fabric
• SQL
• 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.

What You Will Be Doing

• Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering.
• Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking.
• Provide expertise to client senior leadership on innovative Engineering business solutions.
• Strategically engage with client personnel.
• 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.