VILLANOVA UNIVERSITY
Enterprise Data Architect
Villanova University is seeking an experienced Enterprise Data Architect to lead the design, governance, and evolution of the university’s data architecture. The role blends strategic leadership with hands‑on architecture, data modeling, and integration to support institutional decision‑making, analytics, and operations.
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).
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 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.
Qualifications
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., EllucianDS 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).
Master’s degree (preferred).
Certifications in Snowflake, AWS, or data architecture (e.g., CDMP, TOGAF) (preferred).
Experience working in higher education.
Direct experience working with technologies used in enterprise data ecosystems (Ellucian Banner ERP, Snowflake, Power BI, Matillion, Talend, Informatica, AWS, Azure, Collibra, Alation, DevOps, CI/CD).
Villanova University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or other protected characteristic.
#J-18808-Ljbffr
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).
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 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.
Qualifications
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., EllucianDS 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).
Master’s degree (preferred).
Certifications in Snowflake, AWS, or data architecture (e.g., CDMP, TOGAF) (preferred).
Experience working in higher education.
Direct experience working with technologies used in enterprise data ecosystems (Ellucian Banner ERP, Snowflake, Power BI, Matillion, Talend, Informatica, AWS, Azure, Collibra, Alation, DevOps, CI/CD).
Villanova University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or other protected characteristic.
#J-18808-Ljbffr