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# Modeller

- **Company:** Akkodis group
- **Location:** Columbus, OH, United States
- **Experience:** Expert
- **Salary:** $116,480.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Adaptable Database Systems, Artificial Intelligence, Data Analysis, Configuration Management, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Integrity, Metadata, Enterprise Data Management, Model Validation, Information Technology, Data Management, Physical Data Models, Software Version Control, Databricks
- **Published:** November 4, 2026
- **Apply:** https://www.careerbuilder.com/job-details/modeller-columbus-oh--00edec79-1ddf-4663-a2cd-9952c8f2b4d7

## About the Role

Business Intelligence, Artificial Intelligence (AI), Data Modeling, Data Quality, Business Support, Metadata, Documentation, Model Validation, Source Code/Configuration Management (SCM), Change Management, * Bachelor's degree in computer science, Information Systems, Data Engineering, or a related field.

 * 8-10 years of experience in data modeling, data architecture, and enterprise data management.
 * Strong hands-on experience with Databricks, including designing scalable data models for analytics and AI workloads.
 * Proficiency with ERwin or similar data modeling tools, with expertise in logical and physical data modeling.

## Description

Akkodis is seeking a Modeller for a Contract with a client in Columbus, OH/ Jersey City, NJ. The ideal candidate will design and maintain scalable data models that support AI/BI analytics, ensuring data quality, consistency, and performance., * Design and maintain conceptual, logical, and physical data models to support business, AI, and BI requirements.

 * Define entities, relationships, keys, and table structures while ensuring data integrity and consistency.
 * Develop fact and dimension tables optimized for analytics, reporting, and Databricks-based data platforms.
 * Implement data standards, metadata documentation, naming conventions, and validation rules across models.
 * Collaborate with cross-functional teams to manage schema changes, version control, and downstream dependencies.
 * Optimize data models for performance, scalability, and efficient access patterns using ERwin and Databricks.