What are the responsibilities and job description for the Data Resource Analyst position at Michigan State University College of Engineering?
Position Summary
This position is primarily responsible for the end-to-end architecture of dashboards for departmental, divisional, and executive level leadership in Residential and Hospitality Services (RHS). This role focuses on automating data pipelines (Backend) to drive real-time strategic visualizations (Frontend) for high-stakes RHS project portfolios. Other typical daily responsibilities also include data collection, mining, analysis, reporting, and visualization, in conjunction with the Lean Enterprise and Assessment (LEA) team. This position will also support qualitative research methods (e.g., focus groups, interviews).
LEA supports the divisions of RHS and Student Affairs, through a shared services agreement, by managing the full lifecycle of assessment, from instrument design and data collection to analysis and reporting. These insights enable data-informed decision-making for both divisional and unit-level efforts, specifically supporting student success efforts, strategic planning, program development and improvement, continuous process improvement, and innovation.
LEA reports to the Associate Vice President for Residential & Hospitality Services (RHS) and is charged with supporting and advancing a high-performance culture by working with colleagues across the division, and through a shared agreement with Student Affairs, to identify and address student development and student/guest experience excellence opportunities.
This Position Interacts With
Leadership at both the Executive Vice President for Administration (EVPA) and RHS levels: to present and share data, research, data analytics, survey, and process improvement results.
Management: to assist with surveys, research, data analytics, and process improvement requests for their unit.
LEA team: to share information and assist with projects and process improvements.
EVPA and RHS Team Members: to facilitate focus groups, conduct/compile survey results and data analytics, and assist with process improvements.
Dashboards & Data Architecture (45-50% of typical work week)
Dashboard Frontend: Experience translating complex analytical findings into interactive dashboards for data-informed decision making.
Software Mastery: Proficiency in Power BI (DAX/Power Query) or Tableau, SQL and Microsoft Power Platform (PowerApps/Power Automate).
Dashboard Backend Data Connection: Proven ability to collaborate with IT departments to integrate backend systems with institutional data sources, ensuring the successful deployment of dynamic, real-time dashboard features.
Data Architecture & Automation: Proven track record of designing automated workflows and architecting live-syncing data bridges to eliminate manual reporting and data entry.
Assessment & Research (30% of typical work week)
Assessment Proficiency: A strong understanding of the assessment cycle, including creating measurable outcomes, selecting appropriate methodologies.
Research Methods: Proven experience applying both qualitative and quantitative research methods and translating findings into actionable process improvement recommendations and measurable outcome changes to inform institutional change.
Data Visualization (15-20% of typical work week)
Descriptive Analytics: Proficiency in applying descriptive statistics to summarize datasets and identify meaningful patterns or trends in order to assist in operational oversight.
Visual Storytelling: Experience translating complex analytical findings into visuals and reports that inform decision making that make operational abnormalities and project risks immediately visible to leadership.
Performance Indicators Modeling: Expertise in defining and visualizing performance indicators (PIs) that make operational abnormalities and project risks immediately visible to leadership, management and stakeholders.
Technical Communication (5% of typical work week)
Presentation Skills: Proven track record presenting complex data analytics and results effectively to both executive and operational audiences.
All positions in RHS are designated as critical status. In the event of a university closure, modification, or suspension of operations due to snow or other emergency conditions, you will be expected to make all reasonable attempts to report to work as scheduled for the duration of the closure/suspension. If you have an approved remote work agreement to work a portion of your normally scheduled work hours remotely, you may be called upon to work on-site to serve the MSU community. If you have a permanent, on-going, and/or pervasive condition that may impede your ability to work on-site, please contact the Resource Center for Persons with Disabilities (RCPD) at rcpd.msu.edu/get-started.
Minimum Requirements
Knowledge equivalent to that which normally would be acquired by completing one or two years of post-bachelor degree work, such as a Master's in Statistics, Data Analytics, Computer Science, Information Systems, Educational Administration, or a related technical field; three to five years of related and progressively more responsible or expansive work experience in Dashboards & Data Architecture, Assessment & Research, Data Visualization, Technical Communication; or an equivalent combination of education and experience.
Desired Qualifications
Software: Experience with software programs such as SPSS, Stata, Python, R, SAS, NVivo, PowerApps.
Backend Design: direct experience in automated data cleaning and complex relational data modeling.
Process Automation: Ability to design and implement automated workflows.
Predictive Analytics: Knowledge and experience with predictive analytics (Machine Learning).
Statistical Analysis: Proficiency in industry-standard statistical programs (e.g., SPSS, SAS, or JMP).
Lean Awareness: A foundational understanding of Lean principles and continuous improvement mindsets to ensure data collection aligns with process-improvement goals
Knowledge of sophisticated personal computer terminology and operations, and the ability to use e-mail and the Internet.
Equal Employment Opportunity Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.
Required Application Materials
Resume, cover letter, and three (3) professional references.
Work Hours
STANDARD 8-5
Website
CAREERS.MSU.EDU
Bidding eligibility ends May 19, 2026, 11:55 PM
This position is primarily responsible for the end-to-end architecture of dashboards for departmental, divisional, and executive level leadership in Residential and Hospitality Services (RHS). This role focuses on automating data pipelines (Backend) to drive real-time strategic visualizations (Frontend) for high-stakes RHS project portfolios. Other typical daily responsibilities also include data collection, mining, analysis, reporting, and visualization, in conjunction with the Lean Enterprise and Assessment (LEA) team. This position will also support qualitative research methods (e.g., focus groups, interviews).
LEA supports the divisions of RHS and Student Affairs, through a shared services agreement, by managing the full lifecycle of assessment, from instrument design and data collection to analysis and reporting. These insights enable data-informed decision-making for both divisional and unit-level efforts, specifically supporting student success efforts, strategic planning, program development and improvement, continuous process improvement, and innovation.
LEA reports to the Associate Vice President for Residential & Hospitality Services (RHS) and is charged with supporting and advancing a high-performance culture by working with colleagues across the division, and through a shared agreement with Student Affairs, to identify and address student development and student/guest experience excellence opportunities.
This Position Interacts With
Leadership at both the Executive Vice President for Administration (EVPA) and RHS levels: to present and share data, research, data analytics, survey, and process improvement results.
Management: to assist with surveys, research, data analytics, and process improvement requests for their unit.
LEA team: to share information and assist with projects and process improvements.
EVPA and RHS Team Members: to facilitate focus groups, conduct/compile survey results and data analytics, and assist with process improvements.
Dashboards & Data Architecture (45-50% of typical work week)
Dashboard Frontend: Experience translating complex analytical findings into interactive dashboards for data-informed decision making.
Software Mastery: Proficiency in Power BI (DAX/Power Query) or Tableau, SQL and Microsoft Power Platform (PowerApps/Power Automate).
Dashboard Backend Data Connection: Proven ability to collaborate with IT departments to integrate backend systems with institutional data sources, ensuring the successful deployment of dynamic, real-time dashboard features.
Data Architecture & Automation: Proven track record of designing automated workflows and architecting live-syncing data bridges to eliminate manual reporting and data entry.
Assessment & Research (30% of typical work week)
Assessment Proficiency: A strong understanding of the assessment cycle, including creating measurable outcomes, selecting appropriate methodologies.
Research Methods: Proven experience applying both qualitative and quantitative research methods and translating findings into actionable process improvement recommendations and measurable outcome changes to inform institutional change.
Data Visualization (15-20% of typical work week)
Descriptive Analytics: Proficiency in applying descriptive statistics to summarize datasets and identify meaningful patterns or trends in order to assist in operational oversight.
Visual Storytelling: Experience translating complex analytical findings into visuals and reports that inform decision making that make operational abnormalities and project risks immediately visible to leadership.
Performance Indicators Modeling: Expertise in defining and visualizing performance indicators (PIs) that make operational abnormalities and project risks immediately visible to leadership, management and stakeholders.
Technical Communication (5% of typical work week)
Presentation Skills: Proven track record presenting complex data analytics and results effectively to both executive and operational audiences.
All positions in RHS are designated as critical status. In the event of a university closure, modification, or suspension of operations due to snow or other emergency conditions, you will be expected to make all reasonable attempts to report to work as scheduled for the duration of the closure/suspension. If you have an approved remote work agreement to work a portion of your normally scheduled work hours remotely, you may be called upon to work on-site to serve the MSU community. If you have a permanent, on-going, and/or pervasive condition that may impede your ability to work on-site, please contact the Resource Center for Persons with Disabilities (RCPD) at rcpd.msu.edu/get-started.
Minimum Requirements
Knowledge equivalent to that which normally would be acquired by completing one or two years of post-bachelor degree work, such as a Master's in Statistics, Data Analytics, Computer Science, Information Systems, Educational Administration, or a related technical field; three to five years of related and progressively more responsible or expansive work experience in Dashboards & Data Architecture, Assessment & Research, Data Visualization, Technical Communication; or an equivalent combination of education and experience.
Desired Qualifications
Software: Experience with software programs such as SPSS, Stata, Python, R, SAS, NVivo, PowerApps.
Backend Design: direct experience in automated data cleaning and complex relational data modeling.
Process Automation: Ability to design and implement automated workflows.
Predictive Analytics: Knowledge and experience with predictive analytics (Machine Learning).
Statistical Analysis: Proficiency in industry-standard statistical programs (e.g., SPSS, SAS, or JMP).
Lean Awareness: A foundational understanding of Lean principles and continuous improvement mindsets to ensure data collection aligns with process-improvement goals
Knowledge of sophisticated personal computer terminology and operations, and the ability to use e-mail and the Internet.
Equal Employment Opportunity Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.
Required Application Materials
Resume, cover letter, and three (3) professional references.
Work Hours
STANDARD 8-5
Website
CAREERS.MSU.EDU
Bidding eligibility ends May 19, 2026, 11:55 PM