Data Engineer II — Pipelines, Semantics & AI Enablement

University Of Florida; Gainesville (FL); On-site; USD 82,000 - 95,000; Full time

Job summary

University of Florida in Gainesville is seeking an intermediate Data Engineer II to join the Data Platform and Analytics – Data Engineering team. This role focuses on building data pipelines, optimizing data structures, and advancing enterprise metadata and semantic management.

As part of UFIT, you will work closely with customers, analysts, and teammates to translate business requirements into scalable data solutions and semantic models that enable AI-enabled data applications across the

Qualifications

• Requires knowledge of data pipeline methodologies, including ingestion, transformation, integration, and orchestration.
• Understanding of database concepts, functionality, and data modeling principles.
• Familiarity with metadata management, data semantics, and ontology concepts for enterprise data.
• Ability to work with technical and business stakeholders to translate requirements into data/semantic models.

Responsibilities

• Design, develop, and maintain data solutions within UF OneLake.
• Troubleshoot and tune data pipelines and review data synchronization processes.
• Support enterprise metadata management and semantic models for AI-enabled data applications.
• Develop data models and pipelines including near-real-time and batch processes.

Skills

Data pipelines

Metadata management

Semantic modeling

Stakeholder collaboration

Knowledge of databases

Data governance

Education

Associate's degree + 2 years experience; or HS diploma + 4 years experience

Job description

University of Florida in Gainesville is seeking an intermediate Data Engineer II to join the Data Platform and Analytics – Data Engineering team. This role focuses on building data pipelines, optimizing data structures, and advancing enterprise metadata and semantic management.

As part of UFIT, you will work closely with customers, analysts, and teammates to translate business requirements into scalable data solutions and semantic models that enable AI-enabled data applications across the