Motion Recruitment

Data Modeler

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeler with a 6+ month contract in Irving, TX, offering a hybrid schedule. Requires a Bachelor's degree, experience with Oracle and MongoDB, and proficiency in data modeling tools. Financial services experience is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 8, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Irving, TX
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Data Architecture #Databases #Data Integration #MDM (Master Data Management) #MongoDB #Cloud #Agile #NoSQL #Data Management #Oracle Cloud #Security #Computer Science #ERWin #Migration #Physical Data Model #Data Dictionary #Scrum #Scala #Oracle #Data Quality #Database Design #Data Modeling #Data Governance #Metadata #Data Mapping
Role description
Grow your career as a Data Modeler with an innovative global bank in Irving, TX. Contract role with strong possibility of extension and/or conversion. Will require working a hybrid schedule 3 days onsite per week. • Not open to third party employment or sponsorship • Join one of the world's most renowned global banks and trusted brand with over 200 years of continuously evolving financial services worldwide. Will be responsible for designing, implementing, and maintaining data models for our diverse database environments, which include both Oracle (relational) and MongoDB (NoSQL) platforms. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and to learn from you. Contract Duration: 6+ Months Required Skills & Experience • Bachelor's degree in Computer Science, Information Systems, or a related field. • Proven experience as a Data Modeler or Data Architect. • Strong expertise in relational data modeling for enterprise-level systems, preferably in an Oracle environment. • Demonstrable experience in NoSQL data modeling, specifically for document databases like MongoDB. • Proficiency with industry-standard data modeling tools (e.g., Erwin, ER/Studio, Sparx EA, Lucidchart). • A deep understanding of the fundamental differences between relational and NoSQL database design principles. • Excellent analytical and problem-solving skills. • Strong communication and interpersonal skills, with the ability to explain complex technical concepts to both technical and non-technical audiences. Desired Skills & Experience • Experience in the financial services or banking industry. • Knowledge of data warehousing concepts, dimensional modeling, and OLAP. • Familiarity with data governance, data quality, and master data management (MDM) principles. • Experience with cloud database platforms (e.g., Oracle Cloud, MongoDB Atlas). • Understanding of Agile/Scrum development methodologies. What You Will Be Doing • Analyze and translate business requirements into conceptual, logical, and physical data models for both Oracle and MongoDB environments. • Develop and maintain relational data models (ERDs) for our Oracle databases, including defining tables, keys, relationships, and constraints. • Design and document flexible, scalable document-based data models for our MongoDB collections, focusing on optimal structure for application access patterns. • Create and manage the data dictionary and metadata for all models to ensure clarity and consistency. • Collaborate with business stakeholders and analysts to understand and document data requirements. • Work with development teams to ensure they correctly implement and utilize the data models. • Partner with DBAs to optimize data models for performance, scalability, and security. • Establish and enforce data modeling standards, best practices, and guidelines across the organization. • Reverse engineer data models from existing databases to document and understand current data structures. • Evaluate and recommend new data modeling tools and techniques. • Support data integration and migration efforts by providing clear data mappings and transformation logic. • Continuously review and refactor data models to adapt to changing business needs and improve efficiency. Posted By: Melissa Klein