As an essential member of the data services team, this position serves as a key contributor to the foundation’s modern data environment by turning information from multiple sources into reliable, well-organized data that can be used for reporting, decision-making, donor engagement, and emerging AI-supported work.

Core Responsibilities include but are not limited to:

• Prepare and organize data so it can be used responsibly and reliably in AI-supported tools, reporting, and business workflows.
• Collaborate on pilot projects that use AI to improve or speed up data-related work, while ensuring appropriate human review, validation, and data quality controls.
• Design, build, document, and maintain data sets on the cloud data platform that transform source data into clean, consistent, analytics-ready information for business users.
• Develop and improve SQL-based data transformations, ensuring the data platform performs well and produces accurate, dependable results.
• Partner with others to move data into and out of the platform so business systems, reporting tools, and engagement processes receive reliable and well-structured information.
• Identify, investigate, and resolve data quality, reconciliation, and source-system issues including differences in definitions, formats, matching rules, and data relationships.
• Provide responsive support to data users by explaining solutions clearly, documenting procedures, and helping others understand how to use data effectively.
• Stay current on data tools, cloud platform capabilities, and emerging practices that can improve the foundation’s data environment and business outcomes.

Education & Work Experience

• Bachelor’s degree in computer science, MIS, data analytics, or another related field. Equivalent practical experience considered.
• 6-7 years in data engineering, analytics engineering, or BI development, including hand-on SQL development, data modeling, and building data transformations.

Desired Skills & Experience

• Strong SQL and relational data modeling (dimensional/star schema and normalized).
• Experience building ETL/ELT transformations, ideally in a medallion or layered warehouse architecture.
• Familiarity with cloud data platforms and managed data ingestion tools.
• Working conceptual understanding of AI/LLMs and how data quality and structure affect AI outputs; comfort with light prompting and structured-output techniques. Hands-on AI pipeline construction is a plus, not a requirement.
• Experience with cloud data platforms and familiarity with fundraising or higher  education data are a plus.
• Excellent verbal and written communication skills; ability to explain technical topics in business terms.
• Excellent interpersonal and customer service skills.
• Ability to work independently and as part of a team. Must be adaptable, flexible, and self-directed.
• Proficiency with Microsoft Office Suite and ability to learn new software.
• Must be able to handle several activities simultaneously with attention to detail and adherence to deadlines and accuracy.
• Must adhere to strict confidentiality standards.

Travel: None

FLSA Status: Exempt

Location: Ames, IA; potentially hybrid or remote