Enterprise Data Architect

Villanova University•Villanova, PA

31d•Onsite

About The Position

Why work at Villanova? Join a mission-driven organization. Since Villanova University's founding in 1842, we have been inspired by the values of truth, unity, and love, and are a community dedicated to service to others. Villanova has been included among the nation's best colleges and universities. VU's inclusion again in U.S. News & World Report's 2025 "Best Colleges" rankings is another indication of the University's continued prominence and forward momentum. Villanova's most precious asset is our people. As an employee, you will receive a holistic benefits package, generous paid time off, a competitive retirement savings plan, flexible work options, wellness programs including gym membership, professional development, tuition assistance, and more. The Enterprise Data Architect provides technical and strategic leadership in designing, developing, and maintaining the university's enterprise data architecture. This position is responsible for defining data modeling standards, ensuring integration consistency across enterprise systems, and enabling secure, reliable, and high-performing data solutions that support institutional decision-making, analytics, and operations. The role oversees the development of conceptual, logical, and physical data models and collaborates with university stakeholders to ensure data accessibility, quality, and compliance. The Data Architect serves as a key contributor to Villanova's data governance framework and digital transformation initiatives, aligning data strategies with the university's mission and long-term technology roadmap. While the position primarily focuses on architecture strategy, governance, and design, it may include hands-on development work to establish frameworks, prototypes, or migration processes during key implementation phases. Villanova is a Catholic university sponsored by the Augustinian Order. The University is an equal opportunity employer and seeks candidates who understand, respect and can contribute to the University's mission and values.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field
Minimum of ten (10) years of progressive experience in data architecture, data integration, or enterprise data systems.
Demonstrated success designing and implementing large-scale, enterprise data solutions in hybrid or cloud environments.
Proven experience developing enterprise data models, governance frameworks, and integration architectures that support analytics and operational excellence.
Experience collaborating with cross-functional teams across technology, analytics, and data governance domains.
Strong record of leadership in advancing institutional or organizational data capabilities.
Advanced analytical, conceptual, and problem-solving abilities with an enterprise systems mindset.
Ability to lead architecture design discussions, influence technical direction, and communicate effectively with both technical and non-technical stakeholders.
Demonstrated ability to develop and maintain enterprise standards, documentation, and architecture diagrams.
Excellent collaboration, relationship-building, and mentorship skills.
Ability to balance strategic planning with hands-on execution, particularly during foundational or implementation phases.
Deep understanding of enterprise data architecture, data modeling, and integration design across on-premise, hybrid, and cloud environments.
Expertise in ETL/ELT design patterns, API-based integrations, and event-driven architectures.
Knowledge of data governance, metadata management, and master data management frameworks.
Understanding of reporting and analytics environments and how architecture enables advanced data insights.
Deep expertise in enterprise resource planning and student information systems and their data structures and integration strategies (e.g., Ellucian Banner ERP or similar ERP/SIS).
Proven experience with cloud-based data warehousing solutions, including schema design, performance tuning, and security configuration (e.g., Snowflake or similar platform).
Hands-on experience with operational data store and reporting-layer architectures and their integration or migration to modern cloud data environments (e.g., Ellucian Banner ODS to Snowflake or comparable solutions).
Proven success in migrating or modernizing legacy data warehouses or operational data stores to scalable cloud platforms, including schema translation and performance optimization.
Familiarity with cloud infrastructure providers (AWS, Azure, GCP) and data lake architectures.
Strong proficiency in SQL, Python, and ETL tools (e.g., Matillion, Talend, Informatica).
Familiarity with data validation frameworks, reconciliation techniques, and change data capture (CDC) processes.
Comprehensive understanding of security, privacy, and compliance standards relevant to higher education and enterprise environments (e.g., FERPA, GDPR, HIPAA).

Nice To Haves

Master's Degree
Certifications in Snowflake, AWS, or data architecture (e.g., CDMP, TOGAF).
Experience working in Higher Education
Direct experience working with technologies used in enterprise data ecosystems, including: Ellucian Banner ERP and Banner Operational Data Store (ODS) for transactional and reporting data management. Snowflake Cloud Data Warehouse for enterprise analytics, data modeling, and integration. Power BI (or similar tools such as Tableau) for business intelligence and visualization. ETL and integration tools such as Matillion, Talend, or Informatica. Cloud platforms such as AWS or Azure for data storage, orchestration, and analytics.
Experience with data governance tools and frameworks (e.g., Collibra, Alation).
Experience applying DevOps and CI/CD practices to automate and manage data workflows.
Knowledge of higher education data domains (e.g., student lifecycle, enrollment, financial aid, academic records).
Familiarity with real-time data streaming technologies (e.g., Kafka, AWS Kinesis).
Familiarity with data catalogs, data lineage tracking, and data quality programs that support institutional governance.

Responsibilities

Lead the design and implementation of scalable, secure, and high-performing enterprise data architectures aligned with institutional goals.
Develop and maintain conceptual, logical, and physical data models to support operational, analytical, and reporting needs.
Define and enforce enterprise data architecture standards, frameworks, and design principles to ensure interoperability and sustainability.
Design integration strategies and data flow architectures using ETL/ELT, API, and event-driven approaches.
Collaborate with application and integration teams to ensure seamless data flow across academic, administrative, and enterprise systems.
Evaluate and optimize data pipelines for scalability, reliability, and maintainability using modern tools and design patterns.
Guide modernization of legacy data environments into optimized cloud or hybrid architectures.
Engage in hands-on development or prototyping during key implementation phases to establish frameworks and proof-of-concept pipelines.
Document migration procedures, data mappings, and transformation logic for institutional transparency and audit readiness.
Partner with data stewards, system owners, and business units to define and implement enterprise data governance frameworks.
Establish and maintain metadata management, data lineage, and cataloging practices that support discoverability and data quality.
Ensure data integrity, security, and compliance with institutional and regulatory standards (e.g., FERPA, GDPR, HIPAA).
Define governance standards for architecture documentation and metadata to ensure consistency and auditability.
Collaborate with functional and technical teams to validate data accuracy and completeness following migrations or major system changes.
Support the development and operation of data governance committees, contributing to policy creation, enforcement, and continuous improvement.
Collaborate with Information Security and Compliance offices to align with privacy and risk management requirements.
Collaborate with university leadership and cross-functional committees to align enterprise data strategy with institutional objectives and digital transformation goals.
Enable advanced analytics, predictive modeling, and self-service business intelligence through well-structured and governed data ecosystems.
Partner with Institutional Research, Finance, Enrollment, and other functional areas to ensure data solutions meet evolving analytical and reporting needs.
Provide technical leadership and mentorship to integration specialists, analysts, and data governance colleagues across the university, and help establish foundational practices for future data engineering and architecture roles.
Contribute to the university's technology roadmap by evaluating emerging tools, methodologies, and trends in data architecture.
Represent UTS on cross-functional initiatives that advance Villanova's digital transformation and promote data-driven decision-making.
Perform other duties and assist with projects as assigned.