Senior Data Analyst; Part-Time - Information Technology

Overview

APU seeks employees who desire to contribute to our thriving culture by cultivating community through professional interactions, demonstrating a posture of lifelong learning, and modeling Christ-like character. Working together, employees at APU commit to establishing a university atmosphere that is edifying to God and one another.

The Senior Data Analyst is a part-time expert role that supports the University’s advanced reporting, data analytics, and complex problem-solving within the People Soft ecosystem for up to 20 hours per week. This position provides high-level technical insight and hands-on development for analytics needs across HR, Finance, and other related operational areas.

The role is designed for an individual who can step into shifting priorities, quickly understand the dynamic reporting needs of the business, and deliver fast and accurate analytical solutions. This includes deep knowledge of People Soft data structures, strong mathematical reasoning, optimization of large datasets, and high-end scripting for People Soft Portal development. Strategic thinking is essential. Prior experience with APU’s data, historical business rules, and existing reporting patterns is critical to ensure accuracy and continuity.

This position supplements the full-time team by providing senior-level expertise that accelerates delivery and bridges specialized knowledge gaps. This position is part-time, averaging 20 hours per week.

• Required Education

• Bachelor’s degree in Mathematics, Computer Science, Information Systems, Software Engineering, or closely related field.

• Required Experience

• Five to seven years of experience in analytics, data engineering, mathematical modeling, or advanced reporting.
• Expert-level SQL with demonstrated experience tuning complex queries and working with very large datasets.
• Proven hands-on expert-level experience with People Soft HCM, Financials, or Campus Solutions.
• Proven ability to build dashboards, datasets, and reporting tools with accuracy and clarity.
• Experience converting business needs into technical requirements that can be developed quickly.
• Ability to work independently and execute under limited hours while still delivering at a high level.
• Prior experience in higher education environments.
• Prior work with HR, Finance, or Student Systems data.
• Experience mentoring others in SQL, data modeling & analytics, or business intelligence.
• Familiarity with higher-ed systems and historical reporting logic.

• Serve as the senior SME for People Soft reporting, analytics, and data structures.
• Build, tune, and maintain SQL queries, views, and data models used for enterprise reporting.
• Develop Insights dashboards, Pivot Grids, BI Publisher reports, and custom datasets.
• Identify data gaps, isolate root causes, and recommend options for correction.
• Support high-end scripting and portal programming when needed for reporting or automation.
• Translate business questions into clear analytical outputs.
• Provide quick-turn solutions for complex reporting issues and data discrepancies.
• Advise on best practices for data architecture, analytics workflows, and long-term reporting needs.
• Support validation, testing, and rollout of new reporting tools.
• Provide analytics support for strategic university initiatives.
• Mentor COE staff in SQL practices, optimization, and data modeling.
• Other duties as assigned.

• Expert SQL, including performance tuning and working with large and complex datasets.
• Expert knowledge of People Soft table structures, keys, trees, SetID rules, and cross-module dependencies.
• Ability to design dashboards, metrics, and reporting models from concept to delivery.
• Strong analytical thinking with high attention to detail.
• Ability to diagnose issues quickly and recommend efficient solutions.
• Experience with analytics tools such as High Charts, Insights, BI Publisher, or Pivot Grids.
• Clear and direct communication with the ability to explain complex logic in simple terms.
• Strong prioritization and self-management skills in a low-hour, high-output environment.

• Strong analytical reasoning for complex problem solving.
• Highly…