Hybrid Analytics Engineer: Student Success Analytics Job Logan Ohio USA,IT/Tech

Location: Logan

Analytics Engineer - Student Success Overview

Student Success Analytics Engineers play a central role in advancing the university’s analytics capabilities in support of student achievement, learning outcomes, and institutional effectiveness. This position works closely with the Institutional Data Engineering team and the Deputy Chief Data & Analytics Officer to develop and maintain the analytical data models that power predictive analytics, student success reporting, and institutional decision-making.

Student Success Analytics Engineers are responsible for transforming raw institutional data into curated, analytics-ready datasets through the development of a medallion data architecture (bronze, silver, gold layers). These datasets will enable advanced analytics, AI-powered applications, dashboards, and metrics related to student success, student services impact, academic program outcomes, and institutional value.

This position serves as the technical bridge between data infrastructure and analytics users, ensuring that institutional data is modeled, documented, and structured to support high-quality insights for university leaders, faculty, advisors, and student success teams. USU is currently hiring for two positions to support the following areas of the university:

Student Success Division:
In this role the analytics engineer works closely with functional student success teams and leaders to translate operational and student engagement data into scalable analytical models that support student support program assessment, student retention and completion strategies, and continuous improvement efforts. The position will help integrate data from multiple university systems to provide actionable insights, dashboards, and reporting that improve the university’s ability to identify student needs, evaluate interventions, and support student success outcomes across the institution.

Center for Civic Excellence:
In this role the analytics engineer will design, develop, and maintain data models, assessment analytics, and reporting systems that support the measurement and continuous improvement of student learning within the Center for Civic Excellence. This role will work closely with faculty, academic leaders, and center staff to develop scalable approaches for collecting, analyzing, and communicating evidence of student learning outcomes.

The position will help translate assessment and instructional data into actionable insights that inform curriculum development, support data-informed teaching and learning practices, and strengthen the Center’s ability to demonstrate educational quality, student growth, and institutional effectiveness.

This position is eligible for hybrid work within the state of Utah.

Responsibilities

Analytics Data Modeling

Design and maintain analytics-ready data models that support student achievement, learning outcomes assessment, and student success initiatives.
Develop curated data layers within the university’s medallion data architecture to support reporting, dashboards, and predictive analytics (silver and gold layers).
Transform complex institutional data sources into structured analytical datasets suitable for downstream analytics tools. Ensure data transformations are scalable, well-documented, and maintainable.
Optimize data transformations to support high-performance dashboards and analytics applications.
Implement dimensional models and semantic layers to support consistent institutional metrics.

Data Governance and Documentation

Document analytical datasets, transformations, and metric definitions.
Contribute to institutional data governance processes by helping define and standardize key student success metrics.
Ensure analytics data models align with institutional definitions and reporting standards.
Support data quality monitoring and validation processes.

Collaboration and Institutional Impact

Partner with stakeholders to understand analytics needs.
Translate institutional questions about student learning and success into scalable analytics solutions.
Contribute to the development of a modern analytics environment supporting data-informed decision-making across the university.
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