The IR Programmer/Analyst supports data-informed decision-making by developing, maintaining, testing, and improving the programming, data processing, and analytical reporting solutions used by the Office of Institutional Effectiveness (OIE). This programming-intensive role combines applied technical skills with an institutional research and analytical mindset. 

The position writes and maintains code; supports databases, data warehouse structures, data pipelines, dashboards, and automated reporting; participates in technical reviews; and implements data validation and quality assurance procedures. The work helps ensure institutional information is accessible to authorized users, accurate, valid, reliable, secure, and consistently defined. 

The IR Programmer/Analyst works independently on defined assignments and collaboratively with OIE colleagues, Information Technology Services, and university stakeholders. The position contributes to the technical aspects of institutional research, assessment, accreditation, planning, and reporting. It is intended for an early-career to developing mid-level professional with strong foundational knowledge, hands-on experience, analytical curiosity, and capacity for continued growth—not for enterprise-wide systems architecture or senior technical leadership.

Demonstrated experience in the following as shown in application materials:

• Programming and coding. Writing, testing, and troubleshooting SQL queries and using at least one other programming or analytical language or environment (for example, SAS, Python, or R).
• Databases and data development. Experience creating, designing, and modifying database tables; defining table structures and relationships; and working with relational databases, structured datasets, SQL queries, data models, and data warehouse environments.
• Data integration and systems support. Extract, clean, transform, link, and validate data; contribute to automated reporting or database processes.
• Dashboards and reporting. Experience designing, creating, developing, and maintaining interactive dashboards, reports, data visualizations, and analytical datasets using Power BI or comparable tools, with an understanding of hosting, user authentication, access controls, data security, privacy, and secure information sharing.
• Testing and technical review. Reviewing, troubleshooting, and validating code, queries, calculations, or reporting processes, independently or with colleagues.
• Data quality and analytical reasoning. Checking accuracy, consistency, and reliability; examining data relationships and outputs to identify or resolve errors.
• Documentation and collaboration. Documenting technical work and communicating with collaborators or users about analytical or reporting needs. 

• Two years of progressively responsible related programming, database, data engineering, reporting, or business intelligence experience; three or more years demonstrating increased responsibility and independence are especially desirable.
• Advanced degree in a related technical, quantitative, analytical, or educational research discipline.
• Direct hands-on experience with Ellucian Banner, SAS programming, Databricks, and Power BI; equivalent experience with comparable systems and platforms is valued.
• Experience with higher education or institutional research data and measures, including enrollment, student outcomes, faculty, or academic programs.
• Experience with enterprise systems such as Banner, PeopleSoft, Workday, or comparable data environments.
• Experience with cloud data or warehouse technologies such as Databricks, Snowflake, Microsoft Fabric, or comparable platforms, including data pipelines and integration.
• Experience with other visualization and reporting tools (e.g., Tableau or Qlik), version control (e.g., Git), or reusable automated data workflows.
• Familiarity with IPEDS, accreditation, institutional surveys, assessment, or other institutional reporting requirements.
• Experience supporting system transitions, reporting modernization, technical documentation, code review, or data governance practices.