Enterprise Data Modeler

Job Title: Enterprise Data Modeler

Location: Columbus, OH / Wilmington, DE / Plano, TX / Jersey City, NJ

Full Time

Job Description

Enterprise Data Modeler

Role Overview

Design and maintain enterprise analytical data models for BI, OLAP and AI use cases, with clear grain, facts, dimensions, history, metadata, validation and change control.

Key Responsibilities

Define entities, relationships, primary/foreign keys and cardinalities.

Specify row-level grain for fact, event and feature tables.

Design consistent dimension tables, codes, descriptions and hierarchies.

Design fact/event tables with measures, timestamps and join keys.

Represent time and historical changes using effective start/end dates where required.

Standardize naming conventions, data types, units and allowed values.

Maintain metadata including definitions, source, refresh cadence and ownership.

Implement validation rules for nullability, uniqueness, referential integrity and ranges.

Design models for common BI, OLAP and AI access patterns.

Maintain model versioning and update downstream dependencies after schema changes.

Optimize data models for AI and BI performance.

Mandatory Skills

Strong enterprise and dimensional data-modeling experience.

Hands-on fact and dimension design, grain definition and historical modeling.

ER modeling, keys, relationships and cardinalities.

Data governance, metadata and data-quality concepts.

Good understanding of Databricks concepts.

Good understanding of Erwin or an equivalent data-modeling tool.

Preferred Skills

Experience with SCD Type 2 implementation.

Databricks/Delta Lake or lake house modeling experience.

Experience modeling for ML features or AI consumption.

Strong SQL and performance-optimization experience.

Candidate Profile

Hands-on modeler able to explain design decisions clearly.

Strong documentation and change-management discipline.

Able to collaborate with data engineers, BI developers, governance teams and AI teams