Data Modeler

Feuji Inc is a global technology solutions company that strives to be a trusted partner in your digital transformation journey, with a focus on empowering your organization to shift IT from a cost center to a revenue generating powerhouse focused on Cloud, Data science, and Cyber security. We are an Award-Winning IT Professional Services & Consulting firm HQ in Dallas, nearshore office in Costa Rica and have offshore offices in India. Job Title: Data Modeler Location: Remote – Preferred Location: St. Louis, MO Type: 6 Months Contract to Start Requirements & Scope of Responsibility: • Partners closely with data analysts and data engineers to review new source system data and evaluate alignment with the enterprise curated data model. • Adheres to standards, patterns, and best practices for logical and physical data modeling within the enterprise ecosystem. • Analyzes source-to-target mappings and proposes enhancements to core data entities, attributes, and relationships to ensure model extensibility and consistency across domains. • Authors new entities and model changes in SQLDBM (or equivalent modeling tool), maintaining forward-engineering alignment with the Snowflake data warehouse. • Oversees version control, change tracking, and documentation for all model updates, ensuring enterprise visibility and traceability. • Participates in cross-functional design sessions with data analysts, data architects, and business stakeholders to validate model updates and ensure they meet analytical and operational use cases. • Conducts data profiling and collaborates with engineering teams to ensure data quality, completeness, and conformance to model standards. • Provides guidance and guardrails for integrating new data sources into curated layers, balancing flexibility for analytic needs with adherence to enterprise modeling principles. • Works collaboratively with data governance to align model naming conventions, business term definitions, and approved entity relationships. Explicit Non-Ownership (Out of Scope) • Does not own business logic, KPIs, or analytic definitions (these are governed by data analysts or business partners). • Does not execute or manage ETL/ELT pipelines beyond providing transformation logic requirements and model integration guidance. • Does not directly own data quality operations or issue remediation; partners with data engineering or data stewardship teams for action. • Does not act as a project manager or backlog owner for analytics or reporting deliverables. • Does not determine business requirements or success metrics beyond providing technical feasibility and model impact assessments. Thanks & Regards