Data Modeller

Tasks

• Define logical data structures, entities, relationships, and keys.
• Design fact and dimension tables with consistent codes, descriptions, and hierarchies.
• Establish standard date/time fields and effective start/end dates for historical tracking.
• Document field definitions, source systems, refresh frequency, and data ownership.
• Implement data quality and validation checks.
• Design models that support OLAP analytics and AI pipelines.
• Maintain model version history and manage downstream dependencies when schemas change.
• Optimize data models for performance and scalability.

Requirements

• Strong understanding of Data Architecture and Data Modeling.
• Hands-on knowledge of ERwin Data Modeling tools.
• Good understanding of Databricks concepts.
• Expertise in defining entities, relationships, primary keys, foreign keys, and cardinalities.
• Experience designing fact/event tables and dimension tables.
• Understanding of table grain, measures, timestamps, and historical data modeling.
• Knowledge of naming conventions, data types, domains, and data standards.
• Experience with metadata management, data documentation, and schema versioning.
• Understanding of data validation, nullability, uniqueness, referential integrity, and value-range checks.
• Ability to optimize data models for AI/BI workloads, joins, filtering, and aggregations.

How to apply

• Share your updated resume by email.

Location

• Columbus, OH