Enterprise Data Modeler/ Data Architect

Enterprise Data Modeler/ Data Architect
Role Summary
We are seeking an Enterprise Data Modeler / Data Architect to design, govern, and evolve enterprise-wide data models, specifically in the Supply chain area, Inventory Excellence, Transportation and Environmental, Social, and Governance (ESG)
You will be responsible for defining canonical, transactional and dimensional enterprise data models, master and reference data structures, and for ensuring consistent, governed data consumption across operational and analytical use cases.
Key Responsibilities
Enterprise Data Modeling
Design and maintain conceptual, logical, and physical data models using erwin Data Modeler, including subject area models and cross-domain canonical models.
Define and enforce enterprise data standards (naming, normalization, domains, data types).
Maintain data dictionaries, model documentation, and change control processes.
Transactional, Master and Reference Data  systems integration
Model and integrate data from:
Oracle Fusion (Financials, Procurement, AR)
Flintfox (pricing, rebates, claims, agreements)
Microsoft Dynamics CRM (customers, sales, activities)
IBM Order Management System (OMS) (orders, fulfillment, shipment lifecycle)
HighRadius (cash application, credit, collections)
Informatica MDM (Suppler, Customer, Product, Reference)
Create source-to-target mappings, capture transformation logic, and manage schema evolution and metadata lineage.
Stakeholder & Team Leadership
Lead data modeling design workshops with business and technical stakeholders.
Required Qualifications
XX+ years experience in enterprise data modeling and data architecture roles.
Specific experience in Supply chain: Supply chain area, Inventory Excellence, Transportation and Environmental, Social, and Governance (ESG).
Strong hands-on experience with erwin Data Modeler (Latest versions) in large-scale environments is preferred.
Good to have - Experience with Databricks (Delta Lake, Spark, Unity Catalog).
Strong understanding of normalized, dimensional, and canonical modeling approaches.
Experience integrating major enterprise applications (ERP, CRM, OMS, MDM, AR, AP systems).
Good to have - understanding of data governance, data quality, metadata, and lineage.
Excellent communication skills across business and technical audiences.

Core Technology Stack
Modeling: erwin Data Modeler (Required)
Analytics Platform: Databricks (Delta Lake, Unity Catalog), Microsoft PowerBI (Required)
Languages: SQL, Spark SQL, Python / PySpark (good to have)