Executive Director, Data Platforms & Applied AI

Excelsior

United States

Hybrid

USD 120,000 - 130,000

Full time

3 days ago

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Job summary

Excelsior University seeks an Executive Director of Data Engineering and Applied AI to lead the university’s data strategy, architecting and operating data platforms, BI solutions, and AI capabilities in support of institutional priorities.

This senior technology leader partners with university leadership, the Analytics & Data Science team, and enterprise systems to deliver scalable data services, governance, and responsible AI initiatives across the institution.

Qualifications

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field (Master’s degree preferred).
10+ years of experience in data engineering, BI, or enterprise data management, with 5+ years in a leadership role overseeing systems and software design.
Proven experience designing enterprise data systems, integrations, and analytics platforms using modern engineering principles.
Strong technical expertise in data architecture, APIs, middleware, and cloud-native solutions (experience with Microsoft Fabric highly desirable).
Experience with SaaS enterprise systems (e.g., Ellucian Banner, Salesforce) and enabling reporting, analytics, and AI functionalities through secure integrations.
Knowledge of applied AI/ML technologies, including embedded and standalone capabilities within enterprise data environments.
Strong understanding of engineering best practices, including DevOps, CI/CD, version control, automated testing, and secure software development.
Demonstrated experience implementing data governance and compliance frameworks, ideally within higher education.

Responsibilities

Lead the definition, engineering, and execution of the University’s enterprise data strategy, aligning data architecture, platforms, and AI capabilities with institutional goals and digital transformation initiatives.
Design, develop, and maintain robust data and analytics systems, ensuring scalability, security, and performance through modern engineering practices.
Oversee the Data Engineering team, responsible for enterprise data integration, warehousing, BI reporting, and advanced analytics capabilities.
Engineer and sustain a secure, scalable data-as-a-service environment to support operational reporting, advanced analytics, and AI workloads.
Provide technical leadership in software and systems engineering, including integration architecture, API design, and data pipeline development for enterprise systems such as Banner SaaS and Salesforce.
Oversee the full engineering lifecycle of data and analytics initiatives—from requirements analysis and system design through development, testing, deployment, and continuous improvement.
Collaborate with the ADS team to support advanced analytics, machine learning, and AI model integration within the enterprise data ecosystem.
Lead the engineering and governance of applied AI solutions, ensuring infrastructure, data readiness, and policies support responsible and effective AI adoption.