Data Modeler

• Design, develop, and maintain enterprise-level conceptual, logical, and physical data models.
• Make data modeling the primary focus of day-to-day responsibilities.
• Translate business and technical requirements into scalable and efficient data models.
• Define entities, relationships, attributes, keys, constraints, and data structures.
• Ensure data models support enterprise applications, analytics, reporting, and business requirements.
• Collaborate with Data Architects, Data Engineers, Business Analysts, and other technical teams.

MongoDB & Document Data Modeling

• Design and develop document-based data models using MongoDB.
• Demonstrate recent and hands-on experience working with MongoDB.
• Model complex document structures and relationships.
• Design data structures appropriate for NoSQL and document-oriented environments.
• Work with JSON and other semi-structured data formats.

SQL & Snowflake

• Develop and optimize complex SQL queries for data analysis and validation.
• Work hands-on with Snowflake and enterprise data platforms.
• Support data modeling and transformation activities within Snowflake.
• Ensure data structures are optimized for performance, scalability, and usability.

Mortgage & Financial Services Domain

• Apply data modeling expertise to mortgage and financial services data when applicable.
• Mortgage domain experience is strongly preferred but not mandatory.
• Experience with Freddie Mac or Fannie Mae is highly preferred.
• Experience with multifamily mortgage or housing finance data is a strong advantage.
• Understand relationships between mortgage, borrower, property, loan, servicing, and related financial data where applicable.

Data Integration & Enterprise Architecture

• Work closely with data integration and ETL teams.
• Support enterprise data architecture initiatives.
• Understand data flows across source systems, data warehouses, data lakes, and downstream applications.
• Ensure data models align with enterprise architecture and integration requirements.
• Support data quality, consistency, and scalability across enterprise data environments.

Leadership & Problem Solving

• Work independently with minimal direction.
• Demonstrate strong leadership qualities and independent decision-making.
• Proactively identify technical and data-related problems and recommend solutions.
• Bring new ideas and recommendations to improve data modeling processes and solutions.
• Take ownership of deliverables rather than simply executing assigned tasks.
• Communicate technical concepts effectively to both technical and business stakeholders.

Stakeholder Collaboration

• Collaborate with business teams, architects, developers, data engineers, and project leadership.
• Gather and analyze requirements from technical and business stakeholders.
• Explain data modeling decisions and recommendations clearly.
• Participate in architecture discussions, design reviews, and technical meetings.
• Work effectively in consulting and client-facing environments.

We are seeking experienced Senior Data Modelers with strong, hands-on expertise in enterprise data modeling. Data modeling must be the candidate’s primary responsibility, rather than simply an additional skill gained through a Data Engineering role.

Mortgage domain experience is highly preferred but no longer mandatory. The primary focus is on candidates who have strong practical experience designing, developing, and maintaining enterprise data models, including document-based and semi-structured data models.

The ideal candidate should also demonstrate strong leadership, independent thinking, problem-solving, communication, and stakeholder management skills. Candidates should be proactive, capable of bringing ideas to the table, and comfortable working with minimal direction., * Strong, hands-on experience in Enterprise Data Modeling.

• Data modeling should be the candidate’s primary area of responsibility.
• Recent hands-on experience with MongoDB.
• Strong experience designing document-based data models.
• 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 independently with minimal supervision.
• Strong analytical and problem-solving capabilities.
• Demonstrated ability to contribute ideas and proactively solve problems.

Mortgage Domain Experience

• Mortgage experience is highly preferred but not mandatory.
• Recent and consistent involvement in mortgage-related projects is preferred.
• Experience supporting Freddie Mac or Fannie Mae is highly preferred.
• Experience with multifamily mortgage or housing finance data is a bonus.

Bonus / Preferred Skills

• Experience with multifamily 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 with enterprise data architecture.
• Experience working with large-scale and complex data environments.

Soft Skills

• Strong leadership qualities.
• Independent thinker with the ability to make sound technical decisions.
• Proactive problem solver.
• Ability to work with minimal direction.
• Strong communication and presentation skills.
• Ability to bring ideas and recommendations to the team.
• Strong stakeholder management skills.
• Comfortable working with both technical and business teams.
• Ability to take ownership and drive initiatives to completion.