Description

EXPERIENCE

8-10 Years

DESCRIPTION

Role Overview:

The Databricks Data Modeller will be responsible for designing, defining, and optimizing data models to support various analytical and AI/BI use cases. This role involves establishing robust data architecture, ensuring data integrity, and maintaining model performance within a Databricks environment, utilizing tools like ERwin.

Key Responsibilities:

• 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.

Required Skills:

• Good understanding of Databricks concepts.
• Good understanding of tools like ERwin.

Qualifications:

• 8-10 years of experience in data modeling and architecture

Key Skills

Education

Any Graduate