Data Modeler

Job Title: Data Modeler
Location: Jersey City, NJ or Columbus, OH (Onsite)

Erwin tool experience is mandatory 
Define entities, relationships, and keys (primary/foreign keys) and document cardinalities
Specify table grain (row-level meaning) for each fact/event/feature table
Create dimension tables with consistent codes, descriptions, and hierarchy attributes where applicable
Create fact/event tables with measures, timestamps, and join keys to relevant dimensions/entities
Represent time using standard date/time fields and, when needed, effective start/end dates for history
Standardize naming conventions, data types, units, and allowed values (domains) across models
Add metadata and documentation (field definitions, source system, refresh cadence, owner)
Implement basic validation checks (nullability, uniqueness, referential integrity, value ranges)
Design outputs for common access patterns (joins, filters, aggregations) used by OLAP and AI pipelines
Maintain versioning/change history for models and update downstream dependencies when schemas change
Optimize the models for performance of AI/BI use cases
Good understanding of Databricks concepts
Strong work experience of tools like Erwin