- Design conceptual, logical, and physical data models for enterprise retail data platforms.
- Develop and maintain enterprise data models, subject-area models, dimensional models, and canonical data models.
- Use Erwin Data Modeler for data modeling, reverse engineering, forward engineering, and model management.
- Perform data profiling and source-system analysis to understand data structures, relationships, quality issues, and business rules.
- Define data quality rules, Critical Data Elements (CDEs), data standards, and validation requirements.
- Establish and maintain end-to-end data lineage, including source-to-target mappings and transformation logic.
- Define and implement data governance frameworks, including ownership, stewardship, policies, standards, and business glossaries.
- Work with Master Data Management (MDM) teams on Customer, Product, Supplier, Store/Location, and other master domains.
- Define golden records, match/merge rules, survivorship rules, hierarchies, and reference data.
- Develop and maintain business, technical, and operational metadata.
- Collaborate with data engineers, business analysts, data stewards, governance teams, and application architects.
- Perform impact analysis for changes to source systems, data models, integrations, and downstream consumers.
- Ensure data architecture aligns with enterprise architecture, security, privacy, and regulatory requirements.
- Support modernization initiatives involving Data Warehouse, Data Lake, Lakehouse, cloud platforms, and analytics environments.
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
Data & Analytics
Seniority Level:
Not Specified