Why This Role Stands Out
This hybrid role offers you the chance to build cutting-edge AI/ML platforms, contributing directly to impactful use cases and shaping future implementations, with competitive hourly compensation. You'll thrive here if you're a seasoned AI/ML engineer with expertise in Python, data pipelines, and cloud technologies like Azure, eager to collaborate and drive innovation. Apply now to advance your career in a dynamic environment!
Quick Overview
Job Description
Role: Databricks - Genie Agent, Metric View, Semantic, Ontology Architect
Location: Remote
Duration: 12+ Months
Note: Hands-on work is expected from this position.
Requirements:
- Design and implement enterprise ontologies, knowledge graphs, metadata graphs, and semantic relationships to establish the PBM System of Intelligence foundation.
- Build and maintain reusable semantic data models, business glossaries, domain taxonomies, and governed business definitions across PBM domains.
- Build and Design Unity Catalog semantic layer - metric views, and certified KPIs and build Databricks Genie Agents.
- Model complex PBM business domains including Prior Authorization, Claims, Formulary, Clinical Outcomes, Eligibility, and Member data.
- Design knowledge engineering frameworks, context retrieval models, and AI-ready semantic assets supporting Agentic Analytics and conversational intelligence.
- Develop enterprise metadata, lineage, governance, stewardship, and data quality strategies to ensure trusted and auditable AI responses.
- Architect modern cloud-native data platforms leveraging Databricks, Lakehouse architecture, Delta/Iceberg, federated data access, and domain-oriented data products.
- Collaborate with business SMEs, product teams, and AI engineers to translate tribal knowledge into reusable ontology assets, semantic models, and governed intelligence layers.
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