RSC Solutions

Senior Data Modeler with IDA-Hybrid

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Modeler with IDA experience in Jersey City, NJ, offering a hybrid schedule. The contract requires expertise in IBM IDA, Azure, and Databricks, focusing on data modeling, architecture, and integration. Local candidates only.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
April 18, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Jersey City, NJ
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🧠 - Skills detailed
#Strategy #Databricks #Data Access #Data Engineering #Scala #Data Quality #Data Strategy #Physical Data Model #Data Warehouse #Data Modeling #Azure #Documentation #Database Design #Data Integration #Data Architecture
Role description
TITLE: SeniorΒ Data Modeler with IDA experience LOCATION: Jersey City, NJ HYRID 2 DAYS ONSITE NO C2C 3RD PARTY VENDORS!!! NO RELOCATION!! ONLY LOCAL CANDIDATES!! JOB DESCRIPTION: Our direct client is looking for an experienced Data Modeler with hands-on IDA skills to join a growing team. Data Modeler Key Responsibilities: - Design, implement, and optimize data models for the data warehouse, ensuring alignment with business requirements. - Work extensively with β€’ β€’ IBM IDA (InfoSphere Data Architect) β€’ β€’ to create logical and physical data models. - Ensure that the data models are scalable, performant, and aligned with the organization's data strategy. - Collaborate with data engineers to implement and maintain data models in β€’ β€’ Azure β€’ β€’ and β€’ β€’ Databricks β€’ β€’ environments. - Translate business requirements into conceptual, logical, and physical data models, ensuring data quality and consistency across systems. - Participate in data architecture and design discussions to ensure data modeling best practices are followed. - Develop and maintain documentation of data models, data flow diagrams, and database design specifications. - Work with stakeholders to ensure the data models support analytics, reporting, and data integration needs. - Perform impact analysis of changes to existing models and collaborate with teams to assess the effects on downstream systems. - Continuously improve and optimize data models to enhance performance and data accessibility.