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.
Posted By: Jennifer Reynolds