Mandatory: Need candidates with Gen AI used case exposure in Supply Chain manufacturing
Position Summary
The Data Modeler is responsible for designing and maintaining logical and physical data models that support MedTech Supply Chain analytics, reporting, AI, and data product initiatives. This role partners with business stakeholders, data architects, engineers, and analysts to ensure data is structured consistently, efficiently, and aligned to business definitions and governance standards.
Key Responsibilities
Design and maintain conceptual, logical, and physical data models for analytics and reporting solutions.
Collaborate with business stakeholders to understand data requirements and translate them into scalable data structures and data products.
Define and document business entities, relationships, hierarchies, and key metrics.
Work with data engineering teams to support the implementation of data models.
Ensure consistency of data definitions, naming standards, and modeling best practices across the analytics platform.
Support data governance efforts, including metadata management and data lineage.
Participate in data architecture reviews and contribute to platform design decisions.
Assist in evaluating impacts of source system changes on downstream analytics assets.
Required Qualifications
3+ years of experience in data modeling, data warehousing, or analytics engineering.Knowledge of dimensional and normalized modeling methods.
Experience with data modeling tools such as erwin, ER/Studio, or similar.
Understanding of relational databases, data warehouses, and modern cloud analytics platforms.
Strong analytical, documentation, and communication skills.
Hands-on experience with SAP S/4HANA data structures.
Preferred Qualifications
Experience with Databricks on Azure or other cloud data platforms.
Familiarity with semantic layers, business glossaries, and data governance processes.
Experience designing data solutions for AI use cases.
Familiar with the concepts of the Medallion Architecture.
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