Data Architect

The Data Architect serves as the primary architect for the institution’s enterprise data models, data warehouse schemas, and domain data flows. This role translates complex university operations-ranging from student admissions and financial aid to research administration and alumni development-into scalable, high-performance conceptual, logical, and physical data structures. The architect ensures all data design supports institutional reporting, predictive analytics, and emerging AI/ML initiatives while adhering to FERPA, regulatory compliance, and university data governance standards., Data Modeling & Architecture

• Enterprise Blueprinting: Build, maintain, and document enterprise-level conceptual, logical, and physical data models (3NF, Dimensional/Kimball, and Data Vault) spanning major campus domains (Student, HR, Finance, Research, Advancement).
• System Integration Modeling: Model integration pipelines across core Higher Ed systems (e.g., Ellucian Banner, Workday, PeopleSoft, Slate CRM, Canvas LMS, Salesforce).
• Semantic Layer Design: Establish standard data definitions, canonical schemas, and business-friendly semantic layers to power institutional research, executive dashboards, and self-service analytics.
• AI & Modern Data Readiness: Architect clean, well-structured data foundation layers optimized for cloud data warehouses (Snowflake, BigQuery, Redshift, Azure Synapse) and down-stream machine learning/AI applications.

Governance, Security & Quality

• FERPA & Compliance: Ensure all designed schemas enforce strict security controls, row/column-level permissions, and alignment with FERPA, HIPAA, and institutional data privacy rules.
• Data Standards & Metadata: Partner with Data Stewards to create and maintain institutional data dictionaries, business glossaries, and lineage diagrams.

• Architecture Review: Serve on the Architectural Review Board to review source-system schema changes, vendor software integrations, and custom application designs before implementation. Collaboration & Strategy

• Translate complex institutional business rules (e.g., FTE calculations, census reporting, financial aid packaging) into technical specification models.
• Partner closely with Data Engineers, DBAs, and Institutional Research (IR) teams to ensure physical deployment matches architectural blueprints.

• Education: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field (Master’s preferred)., * 6+ years of professional experience in enterprise data modeling (Relational and Dimensional).
• 3+ years of direct experience designing data structures within a Higher Education environment., * Deep familiarity with core Higher Education data domains (e.g., Student Lifecycle, Course Registration, Financial Aid, University Advancement/Donations, Sponsored Research Administration).
• Understanding of Higher Ed operational frameworks (IPEDS reporting, Census dates, Term/Credit hour metrics).
• Data modeling experience across medallion arch in a lakehouse (critical must have). Core domains like HR, Fin, Student etc.

Technical Proficiency:

• Advanced proficiency with enterprise data modeling tools (e.g., Erwin, Enterprise Architect, dbdiagram.io, SqlDBM).
• Understanding, documenting, and diagramming complex systems.
• Strong expertise in cloud data platform architectures (Snowflake, AWS, Azure).
• Advanced SQL, ELT/ETL design concepts, and metadata management solutions.

Preferred Qualifications

• Experience migrating legacy Higher Ed ERPs (e.g., Banner/PeopleSoft) to modern cloud ERPs (e.g., Workday Student) or cloud data platforms.
• Certification in Data Management/Architecture (e.g., CDMP, TOGAF).
• Experience architecting data models for LLMs, RAG applications, or predictive retention models.
• Excellent attitude; self-motivated and principled problem solver; willing to own a problem and see it through to resolution.
• Exp with Fabric (preferred, not required)
• Exp with Boomi (nice to have, not required)