Job Description

Responsibilities*
Data Strategy & Architecture Ownership

Evolve CAI's data architecture strategy to support reporting, analytics, AI/ML, and operational needs
Architect and oversee implementation of end-to-end data warehousing solutions integrating diverse institutional and platform data sources
Establish and enforce standards for dimensional modeling (e.g., Kimball methodology, Star and Snowflake schemas), pipeline design, documentation, and engineering best practices
Ensure cloud data platforms (e.g., Snowflake, Databricks) are optimized for scalability, reliability, cost efficiency, and long-term sustainability
Design and maintain complex ELT frameworks and scalable pipeline patterns
People Leadership & Team Development

Directly manage and mentor Data Engineers and Senior Data Engineers, including performance management, coaching, hiring, and career development
Foster a culture of shared ownership, technical excellence, and continuous learning
Provide technical guidance and architectural oversight across projects, ensuring high-quality delivery and consistency
Plan for team growth and capability development to support CAI's long-term data vision
Governance, Risk & Compliance

Establish and operationalize scalable data governance practices, including standards for data quality, metadata, lineage, and access controls
Ensure compliance with institutional and regulatory data privacy requirements (e.g., FERPA, GDPR) within a higher education environment
Promote strong data stewardship and responsible use of institutional and learner data
Cross-Functional Leadership & Strategic Alignment

Partner with Engineering, Online Learning, XR, and campus stakeholders to translate complex business and academic needs into cohesive data strategies and solutions
Lead discovery sessions with stakeholders and communicate effectively with both technical and non-technical audiences
Align team priorities with CAI's strategic objectives and contribute to roadmap planning within the data domain
Oversee service delivery and stakeholder engagement to ensure responsive, high-impact data support
Innovation & Community Engagement

Evaluate and thoughtfully incorporate emerging technologies, including AI-enabled tools, into engineering workflows and team practices
Co-lead or sponsor initiatives such as the BI + AI Community of Practice and Data Hours to strengthen campus-wide data literacy and collaboration