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Job description
Role: Data Modeler Mode: Onsite Duration: Long term contract Visas: USC/EAD/H1B Location: Jersey City, NJ Relocation: Locals only Note:- Submit EX JPMC local only Job Description: (Must) Job Summary - We are looking for an experienced Data Modeler with strong expertise in the banking domain to design, develop, and maintain enterprise-level data models. The ideal candidate should have deep knowledge of financial data structures, regulatory requirements, and data governance practices, along with hands-on experience in conceptual, logical, and physical data modeling. Key Responsibilities Design and develop conceptual, logical, and physical data models for banking applications such as Retail Banking, Corporate Banking, Risk, Compliance, Payments, and Lending. Work closely with business stakeholders, data architects, and developers to gather and translate business requirements into scalable data models. Develop and maintain data dictionaries, metadata, and data lineage documentation. Ensure data models comply with banking regulations and standards (e.g., BCBS 239, GDPR where applicable). Optimize data structures for performance, scalability, and maintainability. Support data integration, ETL processes, and data warehousing initiatives. Perform data analysis and profiling to ensure data quality and consistency. Collaborate with governance teams to implement data quality and data governance frameworks. Participate in architecture discussions and contribute to enterprise data strategy. Maintain version control and ensure proper documentation of all models. Required Skills & Qualifications Technical Skills Strong expertise in data modeling techniques (ER modeling, dimensional modeling – Star/Snowflake schema). Hands-on experience with tools like: ERwin Data Modeler Informatica PowerDesigner IBM InfoSphere Data Architect Proficiency in SQL and database platforms such as: Oracle, SQL Server, DB2, PostgreSQL Experience with Data Warehousing concepts and ETL tools (Informatica, Talend, etc.). Understanding of Big Data platforms (Hadoop, Spark) is a plus. Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform is an advantage.
