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Data Modeler

ThinklusiveMcLean, VA🇺🇸United StatesPosted 3 Sept 2026

Why This Role Stands Out

This Senior Data Modeler role at Thinklusive offers a fantastic opportunity to shape enterprise data solutions within the mortgage industry, leveraging your extensive experience with relational and NoSQL databases. You'll thrive here if you possess a deep understanding of data modeling principles and a passion for designing robust, scalable data architectures. Join a collaborative team dedicated to data excellence and contribute to impactful projects.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
McLean, VA, United States
Posted
21 hours ago
SnowflakeAgileRoot Cause Analysis

Job Description

Role: Senior Data Modeler (Mortgage)

Location: Mc Lean, VA (5Days onsite)

Required Skills:

Experience:10+ years in Data Modeling, Data Architecture, or Data Management.

  • Strong experience in Data Modeling using relational and NoSQL databases.
  • Expertise in Conceptual, Logical, and Physical Data Model design.
  • Hands-on experience with Dimensional Modeling (Star/Snowflake Schemas) and Data Warehousing.
  • Experience in Data Mapping, Data Lineage, Data Profiling, and Data Quality Analysis.
  • Proficiency in schema design, DDL creation, XML/JSON data structures, and metadata management.
  • Experience with data modeling tools such as ER Studio or equivalent.
  • Knowledge of Snowflake and cloud-based data platforms.
  • Familiarity with Agile development methodologies.
  • Strong analytical, problem-solving, and stakeholder communication skills.

Key Responsibilities:

  • Design, develop, and maintain enterprise data models to support business and analytical needs.
  • Gather and document data requirements from business and technical stakeholders.
  • Create and enhance logical and physical data models, schemas, and database objects.
  • Perform data profiling, lineage analysis, and source-to-target mapping.
  • Analyze and resolve data quality issues through root cause analysis.
  • Develop data flow diagrams, process workflows, and technical documentation.
  • Support data governance, metadata management, and data standardization initiatives.
  • Collaborate with cross-functional teams to deliver scalable, high-quality data solutions.
  • Ensure data models are optimized for performance, scalability, and maintainability.
  • Participate in peer reviews and contribute to data architecture best practices.

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