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# Data Modeler

- **Company:** Syrencloud Llc
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Data Structures, Data Systems, Data Warehousing, Relational Databases, Meta-Data Management, Cloud Services, Data Layers, Data Lineage, SAP S/4HANA, Data Management, Physical Data Models, Meditech, Databricks
- **Published:** August 27, 2026
- **Apply:** https://www.dice.com/job-detail/6d5366b7-6a6f-4851-b2c9-14e1a057a806

## About the Role

* 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.

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.
 * Familiarity with the concepts of Medallion Architecture.
 * Knowledge of SAP S/4HANA data structures is a plus.

## Description

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., * 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.


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