Job Market Guide: Data Modeler jobs in Charlottesville

Competition
Desired Skills
Years of Experience
Years of Experience distribution graph for Data Modelers in Charlottesville. Data Modelers in Charlottesville have between ${} and ${} years of experience, averaging $${} years of experience.

10 Data Modeler jobs in Charlottesville

Alexandria, VA
In this role, you will analyze functional and non-functional business requirements and translate into technical data requirements and create or update existing logical and physical data models.
industry
Energy & Environmental Services
experience
Not Specified

Alexandria, VA
In this role, the selected candidate will conduct a variety of engineering tasks for the development and enhancement of a Web-based decision tool application.
industry
Consulting
experience
Not Specified

Data Modeler

Alexandria, VA
In this role, you will provide data architecture support to include requirement analysis, data modeling and database design to support enterprise business systems.
industry
Business Services
experience
Not Specified

Data Modeler

McLean, VA
The Sr. Data Modeler will work closely with project teams to understand business requirements and provide data modeling subject matter expertise. Strong quantitative and analytic skills are required.
industry
Consulting
experience
8 - 10 years

Data Modeler

Reston, VA
In this role, you will work with the business and product owners to understand new functionality in products.
industry
Consulting
experience
11 - 15 years

Arlington, VA
The Data Modeler Consultant will help devise logical data models, translate them to physical data models, and implement the physical data models needed to support the Pega solution for USMS
industry
Healthcare IT
experience
Less than 5 years

Compensation Estimate

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$80K to $100K - Roanoke, VA
This position is for a Data Modeler with IBM Infosphere.
industry
Consulting
experience
5 - 7 years

Data Modeler

Alexandria, VA
In this role, you will map logical/physical attributes/columns to existing IT systems, identify gaps where data in existing systems do not exist to support the Target Data Architecture (TDA), and identify transformations where data must be altered from the source systems to be accommodated in the TDA.
industry
Financial Services
experience
Not Specified