Data modeler Business/Data Modeler

Data modeler Business/Data Modeler
McLean, VA (5 days Onsite)
6 Months with possible extension
Contract

• Analyze business processes, loan lifecycle stages, and data requirements to define Data Model entities and attributes.
• Leverage existing business information models, source system schemas, and downstream data needs to guide modeling decisions.
• Map and align source system entities to standardized Enterprise Business Model structures, including field definitions and semantic alignment.
• Ensure consistent representation of loan, borrower, property, servicing, and securitization concepts in the enterprise model.
• Collaborate with data governance, engineering, and product teams to validate and refine EBM entities and relationships.
• Reference and incorporate MISMO standards and best practices into the model, ensuring regulatory and industry alignment.
• Maintain model documentation, version control, and traceability of business definitions and transformation logic.
• Support review and approval processes with business stakeholders, modeling working groups, and data architecture teams.

Required Experience:

• 4–7 years of experience in data modeling, business modeling, or information architecture roles.
• Hands-on experience defining logical and conceptual data models, including entity-relationship definitions.
• Strong understanding of the mortgage industry, including familiarity with loan lifecycle, servicing, securitization, or investor reporting processes.
• Prior experience working with Fannie Mae, Freddie Mac, CSS, or similar mortgage ecosystem participants.
• Experience with the MISMO data model, and the ability to apply MISMO concepts to custom enterprise modeling.
• Ability to analyze and reconcile data across business and technical domains.
• Excellent documentation, communication, and stakeholder engagement skills.

Preferred Experience:

• Experience working on enterprise data transformations or modernization programs.
• Familiarity with tools such as ER/Studio, Erwin, or similar modeling platforms.
• Exposure to metadata management tools (e.g., Collibra) and data governance frameworks.\