Executive Director, Data Platforms & Applied AI

Excelsior College

City of Albany (NY)

On-site

USD 120,000 - 130,000

Full time

14 days+
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Job summary

Excelsior University is seeking an Executive Director of Data Engineering and Applied AI to lead the university’s enterprise data strategy, architecture, and platform delivery. This role focuses on secure, scalable data systems and AI initiatives aligned with institutional goals.

Working with ADS and senior leadership, you will guide data integration, BI, analytics, and AI model integration while upholding governance and ethical AI standards across university systems.

Qualifications

  • Bachelor’s degree in a related field; Master’s preferred.
  • 10+ years in data engineering/BI/enterprise data management with 5+ years in leadership.
  • Experience designing enterprise data systems and integrations with modern engineering practices.

Responsibilities

  • Define and execute the university’s enterprise data strategy across data architecture, platforms, and AI capabilities.
  • Lead Data Engineering team for data integration, warehousing, BI, and advanced analytics.
  • Oversee security, scalability, and performance of data and analytics systems.
  • Provide technical leadership in API design and data pipelines for enterprise systems like Banner and Salesforce.
  • Govern data governance, quality, and compliance across institutional systems.
  • Stay current with trends in data, BI, AI, and integration technologies.

Skills

Data architecture
APIs
CI/CD
DevOps
Cloud-native solutions

Education

Bachelor’s degree in CS/SE/IS/Data Eng
Master’s degree preferred

Tools

Microsoft Fabric
Ellucian Banner
Salesforce

Job description

Excelsior University is seeking an Executive Director of Data Engineering and Applied AI to lead the university’s enterprise data strategy, architecture, and platform delivery. This role focuses on secure, scalable data systems and AI initiatives aligned with institutional goals.

Working with ADS and senior leadership, you will guide data integration, BI, analytics, and AI model integration while upholding governance and ethical AI standards across university systems.

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