
Quality Engineer Stefanini
- $25–$29 Per Hour
- Temporary
- Contractor
The AI Data Engineer leverages AI-assisted tools (e.g., code generation, chat-style assistants, agentic workflows) to accelerate pipeline development, documentation, and problem-solving that transforms structured and unstructured data into enterprise-ready assets to power AI and analytics solutions. Built on Microsoft Fabric, Syracuse University's standard data and analytics platform, this role bridges raw data sources with generative AI applications across OneLake, ensuring data quality, compliance, and scalability. Joining an established Enterprise Data & AI team already building in Fabric, the AI Data Engineer serves as a key technical contributor to large-scale, university-wide initiatives, both current and emerging, that advance institutional strategy. At times, the incumbent may be dedicated to specific, university initiatives or partner units based on institutional priorities and cross-departmental projects.
Education and Experience
Skills and Knowledge
Responsibilities
Data Engineering & Pipeline Development
Design and implement scalable pipelines that ingest, clean, transform, and aggregate data from diverse sources (ERP, LMS, research systems, APIs, and external datasets) into formats optimized for AI and analytics. Ensure data quality, integrity, and reproducibility through robust engineering practices.
Integration & Platform Support
Build connectors, workflows, and APIs to unify and operationalize data across cloud and on-premises platforms. Support deployment and lifecycle management of AI/ML models, ensuring seamless integration with enterprise applications.
Governance, Security & Compliance
Maintain metadata, lineage, and documentation to support transparency and auditability. Ensure adherence to Syracuse University's ISF, FERPA, HIPAA, and other regulatory requirements, while applying ethical AI and data governance principles.
Collaboration & Stakeholder Engagement
Gather and translate requirements from academic and administrative units to deliver tailored solutions aligned with institutional priorities. Represent AI/ML teams in cross-campus meetings, working groups, and governance bodies. Deliver presentations and demonstrations to technical and non-technical audiences.
Innovation & Mentorship
Provide technical mentorship on data engineering and integration best practices. Anticipate and scale for future institutional needs (e.g., MCP, serverless, containerization, and generative AI) to drive innovation in data and AI adoption.
Physical Requirements
Not Applicable
Tools/Equipment
Not Applicable
Application Instructions
In addition to completing an online application, please attach a resume and cover letter.
| Location | Syracuse, NY |
