Remote Position
Data Modeler
🌍 Remote · United States
💼 Full-time
The following requirement is open with our client. Title : Canonical Data Modeler - Oracle Retail / Kafka Location : REMOTE Duration :12 Months Relevant Experience (in Yrs.) : Detailed Job Description: Lead end-to-end design of canonical (system-agnostic) data models for core Oracle Retail entities.
- Partner with Catalyst architects and business stakeholders to capture entity attributes, hierarchies, and business rules, and translate them into normalized, versioned schemas.
- Define the crosswalk/ID-mapping strategy between source (RMS) and canonical keys, establish schema versioning and change-management standards for the program.
- Define the schema contract lifecycle; define, document, and publish canonical schemas to a schema registry, ensuring backward compatibility across all consuming applications.
- Drive schema review and formal sign-off from Catalyst leadership and produce data dictionary and governance documentation as lasting program artifacts.
- Assist integration engineering team to ensure canonical models are implementable within the ingestion/transformation pipeline (RMS to raw Kafka topics to canonical topics), advising on schema-registry enforcement and versioning at publish time.
Data Modeling
- Canonical Data Models
- System-Agnostic Data Models
- Normalized Schemas
- Versioned Schemas
- Entity Attributes
- Hierarchies
- Business Rules
Schema Management
- Schema Versioning
- Change Management Standards
- Schema Contract Lifecycle
- Schema Registry
- Backward Compatibility
- Schema Review
- Schema Documentation
Data Governance
- Data Dictionary Documentation
- Governance Documentation
- Formal Sign-off Processes
Data Integration
- Crosswalk/ID-Mapping Strategy
- RMS Integration
- Ingestion/Transformation Pipelines
- Kafka Topics
- Schema-Registry Enforcement
Collaboration
- Catalyst Architects
- Business Stakeholders
- Integration Engineering Teams
- Catalyst Leadership
Must Have Skill Canonical Data Modeling Kafka Business Domain Data Governance Data Integration