Data Warehouse Architect

Designs dimensional data warehouse schemas using Kimball, Inmon, or Data Vault methodologies. Guides star/snowflake schema design, slowly changing dimensions, ETL/ELT patterns, and cloud warehouse optimization for Snowflake, BigQuery, and Redshift.

Gold

v1.0.10 activationsData & AnalyticsTechnologyadvanced

SupaScore

84.6

Research Quality (15%)

8.5

Prompt Engineering (25%)

8.5

Practical Utility (15%)

8.5

Completeness (10%)

8.5

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.5

Best for

▸Design star schema for e-commerce analytics with customer, product, and sales fact tables
▸Migrate legacy Oracle data warehouse to Snowflake with performance optimization
▸Build slowly changing dimension Type 2 tracking for customer address history
▸Create Data Vault 2.0 model for regulated financial services with audit requirements
▸Optimize BigQuery partitioning and clustering for billion-row fact tables

What you'll get

●Complete star schema design with fact and dimension tables, grain definitions, and surrogate key strategies
●Data Vault 2.0 hub-link-satellite model with business rules and loading patterns
●Platform-specific optimization guide with clustering keys, partitioning, and warehouse sizing recommendations

Not designed for ↓

×Building ETL pipelines or writing actual data transformation code
×Setting up cloud infrastructure or managing server configurations
×Creating business intelligence dashboards or visualization layer
×Real-time streaming analytics or operational data stores

Expects

Business requirements, data sources, query patterns, and target cloud platform constraints.

Returns

Dimensional model designs, schema definitions, SCD strategies, and platform-specific optimization recommendations.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

data-warehousedimensional-modelingkimballinmondata-vaultstar-schemasnowflake-schemaslowly-changing-dimensionsetleltsnowflakebigqueryredshift

Research Foundation: 8 sources (3 books, 4 official docs, 1 community practice)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.12/15/2026

Auto-versioned: masterfile quality gate passed (score: 85.5)

v1.0.02/15/2026

Initial release

Works well with

BigQuery Analytics ExpertGold Business Intelligence ArchitectGold Data Pipeline ArchitectGold dbt Analytics EngineerGold Snowflake Analytics EngineerPlatinum

Need more depth?

Specialist skills that go deeper in areas this skill touches.

ETL Pipeline DesignerGold Snowflake Cost Optimization AdvisorGold SQL Performance Tuning ExpertPlatinum

Common Workflows

Enterprise Data Warehouse Implementation

Design dimensional model, implement transformation logic, then build BI layer on top

data-warehouse-architect→dbt Analytics Engineer→Business Intelligence Architect

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