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# Data Modeler

- **Company:** Spectraforce
- **Location:** Phoenix, AZ, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Query Performance, Third Normal Form, Adaptable Database Systems, Data Governance, Data Structures, Data Systems, Data Warehousing, Document-Oriented Databases, Logical Data Models, Reference Data, Salesforce.Com, Cloud Platform System, Er-Win, Git, Data Management, Physical Data Models, Azure Service Fabric, Jenkins
- **Published:** August 4, 2026
- **Apply:** http://leoforce.us/Careers/Spectraforce/JobDetails.html?jobid=0781494c-6fa8-44b4-8cab-4d4a488c790d&OrgId=1&UserId=47

## About the Role

Required Skills : ERWin,GIT,3NF data modeling,Data Modeler,Azure Service Fabric,Jenkins,UCD,Data warehouse
Nice to have skills : Experience with Migration to Salesforce platform

## Description

Job Summary: This hybrid role seeks an experienced data modeler with 8 to 12 years of expertise to design and optimize enterprise data assets for a global organization. The team member will create scalable data models, ensure data quality, and align solutions with business goals while enabling secure and reliable analytics across multiple domains, * Design conceptual and logical data models that align with enterprise standards and enable consistent analytics across multiple business domains

 * Develop physical data models that optimize performance, storage efficiency, and scalability for large volume structured and semi structured datasets
 * Collaborate with product and analytics teams to translate complex business requirements into clear data structures and integration patterns
 * Define and maintain data modeling guidelines that promote reuse, consistency, and compatibility across platforms and applications
 * Coordinate with engineering teams to implement data models on relational and cloud based data platforms while ensuring adherence to architectural principles
 * Review existing data models to identify gaps, redundancies, and improvement opportunities that enhance reliability and reduce maintenance effort
 * Establish data naming conventions, reference data structures, and master data relationships that support unified data understanding across the organization
 * Partner with data governance specialists to document data lineage, critical data elements, and key metadata needed for regulatory and operational compliance
 * Analyze query performance and storage usage to propose indexing, partitioning, and modeling enhancements that improve end user experience
 * Create detailed data design documentation that supports smooth knowledge transfer and consistent implementation by distributed development teams
 * Engage with security and privacy teams to align data models with access controls, retention policies, and protection of sensitive information
 * Support business stakeholders by providing clear explanations of data structures and dependencies that help them make informed decisions based on trusted insights
 * ?Contribute to continuous improvement by evaluating new modeling tools and techniques that can increase productivity and quality of data solutions


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