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
Good understanding of tools like Erwin

Work Authorization
Applicants must be legally authorized to work in the United States. Visa sponsorship may be available for qualified candidates, subject to company policy and applicable immigration requirements.

Equal Employment Opportunity
[Themesoft Inc] is an Equal Employment Opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local law.

Data Modeling

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