Job type
- Full-time
- Quick Apply
Job description
Data Modeler with Erwin Experience
Job Description: client is looking for strong Erwin tool experience.
Role Description:
- 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