- Design and maintain enterprise-wide conceptual, logical, and physical data models.
- Develop dimensional models including Star Schema and Snowflake Schema for analytics and reporting.
- Define business entities, relationships, hierarchies, metrics, and semantic standards.
- Create canonical data models supporting domain-driven data products.
GCP Data Platform Design
- Design data structures for BigQuery-based analytical platforms.
- Support data modeling across Bronze, Silver, and Gold layers of the Lakehouse architecture.
- Define consumption-ready models for BI, self-service analytics, and AI/ML workloads.
- Collaborate with data architects on enterprise data architecture standards.
Data Governance & Metadata
- Define and maintain data lineage, business glossaries, and metadata standards.
- Work with governance teams to ensure compliance with enterprise data policies.
- Drive master and reference data standardization initiatives.
- Support integration of metadata and lineage capabilities through cloud governance tools
- Data Quality & Integration
- Establish data quality rules and validation frameworks.
- Partner with Data Engineers to map source-to-target transformations.
- Conduct impact analysis for source system changes.
- Ensure consistency across ERP, PLM, CRM, Supplier, Finance, and operational datasets.
Business & Analytics Enablement
- Translate business requirements into scalable data models.
- Enable semantic models for BI and reporting platforms.
- Partner with reporting teams to optimize data structures for analytics consumption.
- Support AI-ready and ML-ready data foundation initiatives.
Required Skills
Data Modeling
- Conceptual, Logical, and Physical Data Modeling
- Dimensional Modeling
- Data Vault Modeling (preferred)
- Star & Snowflake Schema Design
- Normalized and Denormalized Data Structures