Onsite Data Modeler - ERwin/Databricks Expert (Contract)

Themesoft Inc; Jersey City (NJ); On-site; USD 124,000 - 179,000; Part time

Job summary

The data architecture team at Themesoft Inc. in Jersey City, NJ is hiring for a contract Data Architect, onsite from day one. The role supports a 6-12+ month engagement with 100% onsite work in Jersey City or Columbus, OH.

You will design data models, metadata, and standards to support AI/BI workloads and ensure robust downstream integration. Responsibilities include defining entities and keys, building dimensional models, and implementing validations across OLAP pipelines, using Databricks and

Qualifications

• Experience designing data models for OLAP/AI pipelines.
• Strong knowledge of dimensional modeling and metadata management.
• Proficiency with tooling like ERwin and Databricks for model implementation.

Responsibilities

• Define entities, relationships, and keys and document cardinalities.
• Create dimension tables with consistent codes, descriptions, and hierarchy attributes.
• Create fact tables with measures, timestamps, and join keys.
• Represent time with date/time fields and history start/end dates.
• Standardize naming conventions, data types, and domains across models.
• Add metadata and documentation (source system, refresh cadence, owner).
• Implement basic validation checks (nullability, uniqueness, referential integrity).
• Design outputs for OLAP and AI pipelines with common access patterns.
• Maintain versioning/change history and update downstream dependencies.

Skills

Databricks

ERwin

Data Architecture and Modeling

Tools

Databricks

ERwin

Job description

The data architecture team at Themesoft Inc. in Jersey City, NJ is hiring for a contract Data Architect, onsite from day one. The role supports a 6-12+ month engagement with 100% onsite work in Jersey City or Columbus, OH.

You will design data models, metadata, and standards to support AI/BI workloads and ensure robust downstream integration. Responsibilities include defining entities and keys, building dimensional models, and implementing validations across OLAP pipelines, using Databricks and