Data Architect

Job Title: Data Architect
Department: Information Technology Services / Data & Analytics
Reports To: Director of Enterprise Data Architecture / Chief Data Officer

Position Summary

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.

Key Responsibilities

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.
 
Required Qualifications
 
•    Education: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field (Master’s preferred).

Experience:
•    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.

Domain Knowledge:
•    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)