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We are seeking an experienced Data Modeler to design and implement high-quality analytical data models that support enterprise reporting, analytics, and data science use cases. The ideal candidate will have hands-on expertise in silver and gold layer modeling, dimensional data warehouse design, and Python automation to streamline data modeling, validation, and documentation processes.
Requirements:
Experience with database modeling tools such as LucidChart
Experience with standard data models such as S-95
Design and develop silver and gold layer data models following medallion architecture principles
Create and maintain dimensional models (Star and Snowflake schemas) for enterprise data warehouses
Define fact and dimension tables aligned with business KPIs and analytical requirements
Apply best practices for slowly changing dimensions (SCDs) and historical data tracking
Lead end-to-end data warehouse design and modeling initiatives
Translate business requirements into scalable, performant data models
Optimize models for query performance, usability, and extensibility
Partner with data engineers to ensure accurate implementation of models
Develop Python-based automation for data model validation, reconciliation and documentation
Automate metadata extraction, schema comparison, and impact analysis
Support automated testing of data models and transformations
Build reusable Python utilities to improve modeling efficiency
Collaborate with data engineers, analysts and architects
Participate in design reviews and ensure alignment with enterprise data standards
Support data governance initiatives including data definitions, lineage, and documentation
Ensure consistency in naming conventions, data types, and modeling standards