Senior Data Architect - School of Medicine

Brigham Young University•Provo, UT

3d•$104,500 - $135,500

About The Position

The Senior Data Architect develops, maintains, and oversees the School of Medicine’s data infrastructure, semantic models, data-quality processes, role-based security, and AI-ready data products. These support evaluation, reporting, accreditation monitoring, and continuous quality improvement. The role works with analytics, evaluation, curriculum, assessment, student progress, IT, and institutional partners so that evidence related to the school’s mission, strategic plan, accreditation, course evaluations, surveys, and aggregate student performance can be accessed, secured, refreshed, validated, and used reliably. It crafts long-term technical strategies aligned with School of Medicine and University objectives and collaborates closely with the School of Medicine Office of Technology and BYU Office of Information Technology. As the School of Medicine launches and grows, the successful candidate must be adaptable and willing to take on evolving responsibilities supporting implementation and ongoing operations. The role supports the school’s vision of fostering a spiritually enriching environment and preparing students for a lifetime of service as Christ-centered physicians. The position requires a firm commitment to BYU’s mission.

Requirements

Firm commitment to the mission of BYU.
Bachelor’s degree in information systems, computer science, business intelligence, data analytics, data science, or a related field, plus 5 years of IT architecture experience; or an equivalent combination of education and/or experience.
Experience with data architecture, data modeling, data integration, automation, data-quality checks, or related analytics engineering work.
Experience documenting data sources, metric definitions, calculation logic, validation steps, and reporting assumptions.
Experience working with sensitive or confidential data and applying appropriate standards for access, use, reporting, and security.
Strong working knowledge of data architecture, data modeling, data integration, data transformation, data quality, cloud data platforms, database management, and business intelligence principles.
Ability to build trusted, reusable, well-documented data products for dashboards, reports, and decision-making.
Proficiency with BI and reporting tools, including the ability to develop dashboards, semantic models, measures, data-quality checks, and refresh processes.
Ability to interpret stakeholder needs and translate them into technical requirements, reporting structures, and data products.
Ability to document data lineage, metric definitions, calculation logic, assumptions, validation steps, and reporting limitations.
Strong problem-solving skills to identify and resolve data-quality, refresh, transformation, calculation, or reporting issues.
Ability to work collaboratively with technical and nontechnical stakeholders.
Sound judgment and discretion when working with sensitive student, faculty, assessment, evaluation, accreditation, and institutional data, including applying information security, identity and access management, data privacy, and governance standards.
Strong written and verbal communication skills.
Demonstrated ability to independently learn, evaluate, and apply emerging technologies, analytics methods, AI capabilities, and data platforms in support of technical leadership and strategic planning in a rapidly changing environment.
Demonstrated curiosity, creativity, adaptability, and commitment to continuous professional growth and innovation.
Familiarity with AI-enabled analytics tools and responsible-use practices for data modeling, validation, documentation, summarization, and analysis workflows.

Nice To Haves

Experience developing dashboards, data models, reports, or analytics products using BI tools.
Experience with Microsoft Fabric, Power Automate, Power Query, DAX, SQL, Power BI, dataflows, semantic models, or comparable platforms.
Experience creating role-based dashboards or reporting layers for multiple stakeholder groups.
Experience developing AI-ready data models, self-service analytics structures, or documentation to support AI-assisted analysis.
Experience collaborating with IT, institutional research, academic programs, data owners, and nontechnical stakeholders.
Experience in higher education, health professions education, institutional research, student information systems, assessment systems, survey systems, curriculum systems, or learning management systems.
Knowledge of Microsoft Fabric, Power Automate, Power Query, DAX, SQL, Power BI, semantic models, role-level security, and/or dataflows.
Knowledge of FERPA-sensitive educational data, role-based reporting, de-identification practices, minimum response thresholds, or data governance principles.
Familiarity with medical education, educational outcomes, assessment data, course/faculty evaluations, curriculum data, accreditation monitoring, or CQI reporting.
Ability to support self-service analytics by creating trusted models, documentation, definitions, and user guidance.
Relevant certifications or training in Microsoft Fabric, Azure data tools, data analytics, data engineering, data governance, business intelligence, or related areas.

Responsibilities

Design, develop, maintain, and provide strategic oversight for trusted educational data architecture supporting the Office of Analytics and Evaluation.
Build semantic models and curated data structures for dashboards, reports, accreditation monitoring, continuous quality improvement tracking, survey reporting, and student outcomes analysis.
Translate evidence needs related to mission fulfillment, strategic priorities, accreditation compliance, program evaluation, course evaluations, and student performance into reliable data models and reporting structures.
Develop and maintain data dictionaries, metric definitions, measure logic, and documentation.
Structure data products to support accurate, explainable, confidential, and secure analysis.
Design, develop, and maintain trusted educational data architecture for assigned operational areas of the School of Medicine.
Develop and maintain automated data integration, transformation, and refresh processes.
Partner with SoM IT, OIT, CTL, the Registrar, Curriculum and Assessment, Student Progress, and others to support reliable source-system connections and data flows.
Build and maintain data-quality checks, reconciliation processes, exception reports, and validation workflows.
Identify data inconsistencies, missing data, definition conflicts, and reporting risks, and coordinate their resolution with appropriate stakeholders.
Support automation of recurring reporting workflows to reduce manual reporting and improve reliability.
Establish systems and directives for monitoring software and system architecture performance.
Research, inform, and direct architectural changes to meet industry standards, regulatory requirements, and security and privacy mandates.
In cooperation with IT, build and maintain technical infrastructure, semantic models, data pipelines, refresh processes, role-based security, and reusable dashboard and reporting frameworks.
Configure role-based access and security consistent with approved data governance, confidentiality, de-identification, and appropriate-use standards.
Support dashboards and reports for committees, curricular review, strategic plan monitoring, accreditation monitoring, and other school needs.
Ensure dashboards and reports clearly communicate definitions, filters, data limitations, and refresh information.
Maintain report dependencies, version control, and technical documentation for major analytics products.
Prepare data products, reporting structures, and governance frameworks for responsible self-service and AI-assisted analytics.
Collaborate with staff and stakeholders to understand reporting needs, translate questions into technical requirements, and support appropriate use of analytics products.
Help faculty, staff, and other stakeholders develop the skills and confidence to create, interpret, and communicate analytics using approved tools, data sources, and standards.
Lead and coordinate advanced troubleshooting with users and stakeholders and resolve issues during design and implementation.
Develop reusable templates, documentation, data dictionaries, and guidance to promote consistent use of metrics and reporting practices.
Guide users in applying approved definitions, data-quality expectations, confidentiality requirements, and appropriate-use standards.
Review or advise on user-created analytics as needed to confirm accuracy, consistency, and responsible interpretation.
Monitor and evaluate opportunities to use AI-enabled tools, automation, and emerging technologies to improve analytics workflows and decision support.
Evaluate emerging technologies, analytics methods, and AI capabilities and identify opportunities to strengthen data infrastructure, analytics services, and decision support.
Support continuous learning and improvement initiatives that optimize service delivery, strengthen data-driven decision-making, and improve reporting processes.

Benefits

BYU automatically contributes 8% to the 401(k) at no cost to the employee; if the employee contributes 5%, BYU adds an additional 4%. Rehires may qualify for different retirement plans.
13 paid holidays, 22 days of paid vacation, and 12 sick days accrued annually.
Employee assistance program available to the employee and all household members.
Tuition benefits for employees and eligible family members.
Access to athletic facilities.
Medical and dental benefits.
Short- and long-term disability benefits.
Paid parental and maternity leave.
Wellness program.
Free on-campus parking.
Free UTA passes for employees, spouses, and qualified dependents.
Discounts at the BYU Store and for many BYU events.