Role : Erwin Data Modeler / Data Architect

Work model : Hybrid

Role Summary :

We are seeking an Enterprise Data Modeler / Data Architect to design, govern, and evolve enterprise-wide data models, master data, and reference data across a complex transactional and analytical landscape.

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.

Master Reference Data Management :

- Architect and implement Master Data Management (MDM) solutions using Informatica MDM, covering Customer, Product, Supplier, Pricing, and Party domains.

- Design golden record, match - merge rules, survivorship logic, and source system trust frameworks.

- Define and manage reference data models (code sets, hierarchies, value lists) using Informatica R360.

- Establish stewardship workflows, data governance alignment, and lifecycle management for master and reference data.

Data Architecture Databricks Lakehouse :

- Define data architecture patterns for Databricks Lakehouse using Delta Lake, Unity Catalog, and medallion architecture.

- Translate enterprise transactional and MDM models into optimized analytical schemas and data marts.

- Partner with data engineering teams to implement ELT/ETL pipelines with data validation and reconciliation.

Required Qualifications :

- 10+ years experience in enterprise data modeling and data architecture roles.

- Strong hands-on experience with erwin Data Modeler in large-scale environments.

- Experience with Databricks (Delta Lake, Spark, Unity Catalog).

- Advanced SQL and strong understanding of normalized, dimensional, and canonical modeling approaches.

- Experience integrating major enterprise applications (ERP, CRM, OMS, MDM, AR systems).

- Strong understanding of data governance, data quality, metadata, and lineage.

Core Technology Stack :

- Modeling : erwin Data Modeler

- Analytics Platform : Databricks, Microsoft PowerBI

- Languages : SQL, Spark SQL, Python / PySpark

- Governance/Data Quality : Unity Catalog, Informatica DG/DQ