DataBricks/UC Data Modeler

Abacus Insights

8h•Remote

About The Position

We are looking for a DataBricks/UC Data Modeler to join a global data modeling team responsible for transforming business requirements into conceptual, logical and physical data models. This role supports ongoing and new AI initiatives as they relate to the Abacus data model and metadata. We are seeking experience in healthcare data domains (Claims, Membership, Enrollment, Provider, Billing, Interoperability - FHIR, HL7, ADT, CCDA, etc.), as well as experience with enterprise data modeling and Databricks Unity Catalog. This role requires knowledge of healthcare analytics such as total cost of care, provider attribution, payment integrity, risk adjustment, HEDIS/Stars, billing, and/or financial performance. The role will work closely with the Director of Data Modeling and Senior Data Modelers to adhere to data modeling standards, metadata governance, and follow data architecture strategies that align with business and technical needs. They will also collaborate with business analysts, product analysts, client implementation teams, and data governance teams to ensure models align with industry standards, support regulatory, operational and analytic use cases, are highly performant, and support data integrity initiatives. The DataBricks/UC Data Modeler will enable Unity Catalog features to promote metadata management, data discovery, views and business metrics, in support of RAG, SQL Agent, and AI initiatives. They should be familiar with context engineering. This is an exciting opportunity for a healthcare data modeler with experience in AI, Databricks, Snowflake, and modern data engineering practices to shape the future of healthcare data platforms.

Requirements

Hands-on experience with Databricks Unity Catalog, cloud data platforms (Databricks, Snowflake), and Lakehouse architectures.
Knowledge of data governance, security, and regulatory compliance in healthcare data management.
2+ years in data modeling and cloud-based data engineering or reporting.
Proficiency with enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar).
Understanding of healthcare data domains: Core Payer (Claims, Membership, Enrollment, Provider, Billing, Premium) and Clinical Interoperability (FHIR, HL7, ADT, CCDA).
Experience with schema evolution, lossless modeling, and data versioning strategies.
Strong SQL skills, data profiling, and metadata management.
Ability to learn from senior modelers, enforce best practices, and drive adoption of enterprise data standards.
Excellent collaboration skills with data architects, engineers, and client implementation teams.

Nice To Haves

Background in healthcare reporting or healthcare data engineering is strongly preferred.
NoSQL data model experience.
Python coding skills.
Knowledge of APIs, SDKs, and distributed data frameworks for enabling real-time and micro-batch processing of structured, semi-structured and unstructured data.

Responsibilities

Define requirements for canonical data models, semantic layers, metadata, and ontologies for enterprise healthcare customers.
Build and manage semantic layers using Databricks Unity Catalog; register AI assets and metrics.
Develop and test semantic layers leveraging AI Assistant and SQL Agents.
Design conceptual, logical, and physical data models aligned with enterprise architecture and industry standards.
Apply best practices for schema evolution, metadata management, and data versioning.
Ensure models support analytical (data science, actuarial, reporting) and operational (claims, care management) use cases.
Maintain metadata, glossaries, ER diagrams, and data dictionaries for governance and lineage.
Collaborate with Client Management, Product, and Business Analysts to assess impact and meet client expectations.
Provide data model expertise during client implementations and perform data profiling.
Utilize SQL and data integrity principles throughout modeling activities.
Lead and mentor engineering teams (30+ engineers), evolving structure for scale toward 50+.
Drive innovation in AI and data engineering, ensuring roadmap delivery and operational excellence.