Must Have Technical/Functional Skills

Skills / Requirements:

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

Salary Range $120,000-$130,000 a year