Data Modeler

We are seeking a highly experienced Senior Data Modeler with strong hands-on expertise in enterprise data modeling, MongoDB, Snowflake, SQL, JSON/semi-structured data, and mortgage domain data., * Design, develop, and maintain enterprise-level conceptual, logical, and physical data models.

• Create data models for both structured and semi-structured data, including JSON and document-based data.
• Design and work with MongoDB document-based data models.
• Develop and optimize data structures and models using Snowflake and SQL.
• Analyze business and technical requirements and translate them into scalable enterprise data models.
• Collaborate with Data Engineering, Architecture, Business, and Technology teams to ensure data models align with enterprise standards.
• Contribute to data integration, ETL, and enterprise data architecture initiatives.
• Work with mortgage and housing finance data and understand the relationships between business processes, data entities, and systems.
• Identify data quality, consistency, and modeling issues and proactively recommend solutions.
• Communicate complex data concepts effectively to both technical and business stakeholders.
• Work independently, demonstrate strong problem-solving skills, and contribute ideas and recommendations beyond assigned tasks.

The ideal candidate will have a proven track record where data modeling has been their primary responsibility, rather than being a secondary skill within a Data Engineering role. Strong experience in the mortgage/housing finance domain is essential, with experience supporting Freddie Mac or Fannie Mae highly preferred., * Strong, hands-on experience in Enterprise Data Modeling as a primary responsibility.

• Recent hands-on experience with MongoDB, particularly document-based data modeling.
• Strong and recent Mortgage Domain / Housing Finance experience.
• Experience with Freddie Mac or Fannie Mae is highly preferred.
• Strong proficiency in SQL.
• Hands-on experience with Snowflake.
• Experience modeling JSON and semi-structured data.
• Strong understanding of Data Integration, ETL, and Enterprise Data Architecture.
• Excellent communication and stakeholder management skills.
• Ability to work effectively with both technical and business teams.
• Strong leadership, independent problem-solving, and decision-making abilities.

• Ability to work onsite in McLean, VA. Preferred / Bonus Qualifications

• Experience with Multi-Family Mortgage or Housing Finance data.
• Familiarity with Data Governance and Data Quality frameworks.
• Exposure to cloud-based data platforms beyond Snowflake.
• Experience working in consulting or client-facing environments.
• Experience working with financial services or mortgage-related enterprise data environments.