Knowledge Graph Engineer (Azure / Databricks)
Industry: Health Insurance / Healthcare (Regulated Environment)
Role Type: Contract (6–12 months, strong potential to extend or convert)
Experience Level: Expert / Senior Individual Contributor
Work Hours: Core business hours (8:00 AM – 5:00 PM CST)
Project Overview
This engagement supports a large, regulated healthcare organization modernizing its data and analytics ecosystem through production‑grade knowledge graph solutions. The Knowledge Graph Engineer will play a hands‑on, execution‑focused role, designing and delivering semantic graph architectures that enable trusted analytics, cross‑domain insight, and AI‑driven use cases.
The project is centered on building and operating lakehouse‑driven knowledge graphs on Azure, leveraging Databricks, Spark, and Delta Lake. These graphs will serve as a semantic foundation for analytics, APIs, and downstream AI applications—moving beyond conceptual modeling into real, production outcomes.
This role is ideal for an independent, proactive engineer who has personally built and delivered knowledge graphs end‑to‑end, can articulate architectural trade‑offs, and thrives in environments requiring accountability, ownership, and close collaboration with technical and business stakeholders.
Key Responsibilities
• Design, implement, and deliver production knowledge graph solutions, including entities, relationships, and semantic meaning
• Translate complex business and domain concepts into analytics‑ready graph models that support traversal, inference, and AI enablement
• Build and operate lakehouse‑driven graph construction pipelines using Databricks, Spark, and Delta Lake
• Design architectures that support
• Batch graph analytics in the lakehouse
• Low‑latency graph traversal for APIs and downstream consumers
• Make and clearly articulate architectural trade‑offs, including when and why a graph approach is appropriate
• Partner closely with engineering, analytics, and business teams to ensure the semantic layer delivers usable, trusted outcomes, not just models
• Contribute to semantic consistency, lineage, traceability, and governance as platforms mature
Required Skills & Experience (Must‑Have)
• Proven hands‑on experience designing and implementing knowledge graphs in production environments
• Strong understanding of semantic and graph modeling concepts beyond traditional relational schemas
• Ability to translate complex healthcare, insurance, or operational domains into graph‑based solutions
• Experience working with large, multi‑domain datasets in regulated environments
• Strong hands‑on experience with Databricks, including Spark‑based, lake house‑driven pipelines
• Advanced SQL skills and experience with distributed data processing
• Strong ownership mindset with a bias toward delivery, execution, and accountability
Preferred / Strong Plus Experience
• Hands‑on experience with Azure‑based graph technologies, such as:
• Azure Cosmos DB (Gremlin API or equivalent)
• Neo4j or comparable graph platforms
• Experience designing systems that support:
• Batch graph analytics
• Low‑latency graph traversal for APIs or consumer‑facing applications
• Familiarity with ontologies, semantic layers, and controlled vocabularies
• Experience applying AI/ML techniques to knowledge graphs, including natural language or conversational access
Nice to Have
• Experience operating, supporting, or governing production knowledge graph platforms
• Ability to optimize graph models and queries for scale and performance
• Experience establishing semantic consistency, lineage, and traceability across analytics environments
• Ability to mentor engineers and provide architectural guidance while remaining hands‑on
What Success Looks Like
• You have personally built and delivered knowledge graphs used in real analytics, operational, or AI‑enabled use cases
• You can clearly explain
• Why a graph approach was chosen
• How the semantic layer unlocked cross‑domain insight or AI capabilities
• You deliver usable intelligence, not just nodes and edges
Additional Notes
• Background in healthcare, insurance, financial services, or other regulated industries is highly valued
• This role requires an independent driver—someone proactive, architect‑level in thinking, and hands‑on in execution
• Open to consultants outside select states; must be available during CST business hours
• Long‑term opportunity with significant ongoing work and growth potential
Job Type & Location
This is a Contract position based out of Omaha, NE.
Pay And Benefits The pay range for
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Role Type: Contract (6–12 months, strong potential to extend or convert)
Experience Level: Expert / Senior Individual Contributor
Work Hours: Core business hours (8:00 AM – 5:00 PM CST)
Project Overview
This engagement supports a large, regulated healthcare organization modernizing its data and analytics ecosystem through production‑grade knowledge graph solutions. The Knowledge Graph Engineer will play a hands‑on, execution‑focused role, designing and delivering semantic graph architectures that enable trusted analytics, cross‑domain insight, and AI‑driven use cases.
The project is centered on building and operating lakehouse‑driven knowledge graphs on Azure, leveraging Databricks, Spark, and Delta Lake. These graphs will serve as a semantic foundation for analytics, APIs, and downstream AI applications—moving beyond conceptual modeling into real, production outcomes.
This role is ideal for an independent, proactive engineer who has personally built and delivered knowledge graphs end‑to‑end, can articulate architectural trade‑offs, and thrives in environments requiring accountability, ownership, and close collaboration with technical and business stakeholders.
Key Responsibilities
• Design, implement, and deliver production knowledge graph solutions, including entities, relationships, and semantic meaning
• Translate complex business and domain concepts into analytics‑ready graph models that support traversal, inference, and AI enablement
• Build and operate lakehouse‑driven graph construction pipelines using Databricks, Spark, and Delta Lake
• Design architectures that support
• Batch graph analytics in the lakehouse
• Low‑latency graph traversal for APIs and downstream consumers
• Make and clearly articulate architectural trade‑offs, including when and why a graph approach is appropriate
• Partner closely with engineering, analytics, and business teams to ensure the semantic layer delivers usable, trusted outcomes, not just models
• Contribute to semantic consistency, lineage, traceability, and governance as platforms mature
Required Skills & Experience (Must‑Have)
• Proven hands‑on experience designing and implementing knowledge graphs in production environments
• Strong understanding of semantic and graph modeling concepts beyond traditional relational schemas
• Ability to translate complex healthcare, insurance, or operational domains into graph‑based solutions
• Experience working with large, multi‑domain datasets in regulated environments
• Strong hands‑on experience with Databricks, including Spark‑based, lake house‑driven pipelines
• Advanced SQL skills and experience with distributed data processing
• Strong ownership mindset with a bias toward delivery, execution, and accountability
Preferred / Strong Plus Experience
• Hands‑on experience with Azure‑based graph technologies, such as:
• Azure Cosmos DB (Gremlin API or equivalent)
• Neo4j or comparable graph platforms
• Experience designing systems that support:
• Batch graph analytics
• Low‑latency graph traversal for APIs or consumer‑facing applications
• Familiarity with ontologies, semantic layers, and controlled vocabularies
• Experience applying AI/ML techniques to knowledge graphs, including natural language or conversational access
Nice to Have
• Experience operating, supporting, or governing production knowledge graph platforms
• Ability to optimize graph models and queries for scale and performance
• Experience establishing semantic consistency, lineage, and traceability across analytics environments
• Ability to mentor engineers and provide architectural guidance while remaining hands‑on
What Success Looks Like
• You have personally built and delivered knowledge graphs used in real analytics, operational, or AI‑enabled use cases
• You can clearly explain
• Why a graph approach was chosen
• How the semantic layer unlocked cross‑domain insight or AI capabilities
• You deliver usable intelligence, not just nodes and edges
Additional Notes
• Background in healthcare, insurance, financial services, or other regulated industries is highly valued
• This role requires an independent driver—someone proactive, architect‑level in thinking, and hands‑on in execution
• Open to consultants outside select states; must be available during CST business hours
• Long‑term opportunity with significant ongoing work and growth potential
Job Type & Location
This is a Contract position based out of Omaha, NE.
Pay And Benefits The pay range for
Apply tot his job
Apply To this Job