Enterprise Data Modeler

Tata Consultancy Services; Columbus (OH); On-site; USD 90,000 - 120,000; Full time

Job summary

Tata Consultancy Services Limited in Columbus, OH, seeks an Enterprise Data Modeler to design and maintain enterprise analytic data models for BI, OLAP and AI use cases, with clear grain, facts, dimensions, history, metadata and change control.

You will define entities, relationships, keys, grain; design dimensions and hierarchies; and implement time-based history, data governance and quality controls. Proficiency in Databricks, Delta Lake and Erwin is preferred.

Qualifications

• Strong enterprise and dimensional data-modeling experience.
• Hands-on fact and dimension design with history modeling.
• ER modeling, keys, relationships and cardinalities.
• Data governance, metadata and data-quality concepts.
• Familiarity with Databricks concepts.
• Experience with Erwin or equivalent data-modeling tool.

Responsibilities

• Design and maintain enterprise analytical data models for BI, OLAP and AI use cases.
• Define entities, relationships, keys and grain for fact and dimension tables.
• Design dimension tables, hierarchies, codes and descriptions.
• Represent time with effective start/end dates and history tracking.
• Maintain metadata including definitions, sources and ownership; ensure validation and change control.
• Optimize models for AI and BI performance and update downstream dependencies.

Skills

Enterprise data modeling

Dimensional modeling

ER modeling

Data governance

Metadata management

SQL

Databricks concepts

Erwin

Data quality

Tools

Erwin

Databricks

Delta Lake

Job description

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.