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# Enterprise Data Modeler Databricks

- **Company:** Proteam Solutions
- **Location:** Dublin, OH, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Amazon Web Services, Data Analysis, Microsoft Azure, Data Governance, Data Vault Modeling, Dimensional Modeling, Enterprise Architecture Framework, Metadata, Cloud Services, Enterprise Data Management, Google Cloud, Snowflake, Data Management, Physical Data Models, Databricks
- **Published:** July 4, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=80defc3f073776f9

## About the Role

* Strong expertise in enterprise data modeling.
 * Hands-on experience with Databricks and Medallion Architecture.
 * Experience designing conceptual, logical, and physical data models.
 * Strong knowledge of Snowflake or similar cloud data warehouse platforms.
 * Experience with ERwin, ER/Studio, or comparable data modeling tools.
 * Knowledge of dimensional modeling (Kimball).
 * Experience with Data Vault methodologies.
 * Strong understanding of metadata, lineage, governance, and data quality., * Experience with enterprise architecture frameworks.
 * Knowledge of Azure, AWS, or Google Cloud.
 * Experience supporting enterprise data governance programs.
 * Strong communication and stakeholder management skills.
 * Experience modeling across multiple enterprise business domains.

## Description

We are seeking an experienced Enterprise Data Modeler with deep expertise in Databricks and modern cloud data platforms. This role will focus on designing scalable enterprise data models that support analytics, governance, and business intelligence initiatives across multiple business domains. The ideal candidate understands Medallion Architecture, dimensional modeling, enterprise data standards, and modern lakehouse architectures., * Design conceptual, logical, and physical enterprise data models.

 * Develop scalable models supporting cross-functional business domains.
 * Establish enterprise data modeling standards and naming conventions.
 * Collaborate with business stakeholders to translate requirements into scalable data models.
 * Ensure alignment with enterprise data architecture and governance standards.
 * Integrate metadata, lineage, and data quality principles into model designs.
 * Partner with Data Engineers implementing solutions within Databricks.
 * Support enterprise analytics initiatives across cloud data platforms.


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