Senior Data Modeler / Data Architect
- Location
- Across United States
- Salary
- Not specified
- Company
- Akash pawar
Job description
Role & Company / Project Overview: We are seeking a highly experienced Senior Data Modeler / Data Architect with strong Finance domain expertise and hands-on experience building Snowflake-based Silver and Gold layer data models. The candidate will lead stakeholder workshops, challenge existing data models, and define future-state data modeling best practices rather than just documenting requirements. Key Responsibilities & Daily Duties: • Lead stakeholder workshops and challenge existing data models. • Define future-state data modeling best practices. • Design, develop, and maintain logical and physical data models. • Implement dimensional modeling and normalization techniques. • Build and optimize Snowflake-based Medallion Architecture data models across Silver and Gold layers. • Work directly with General Ledger (GL) and Trial Balance data from ERP source systems. Required Qualifications, Skills & Experience: • 10+ years of professional experience in data modeling and data warehouse architecture. • Must-Have Expertise in Finance Data Modeling (most critical). • Strong hands-on experience with Snowflake Data Modeling. • Deep knowledge of Medallion Architecture (Silver & Gold Layers). • Demonstrated proficiency in Logical & Physical Data Modeling, Dimensional Modeling, and Normalization Techniques. • Comprehensive understanding of ERP Source Systems (SAP, Oracle, JD Edwards), specifically General Ledger (GL) and Trial Balance data. • Strong background in Data Warehouse Architecture and proficiency with Data Modeling Tools. • Proven track record in Stakeholder Management & Workshop Leadership. • Eligibility: W2 Candidates Only (US Citizens / Green Card holders). Working Hours, Shifts & Location Details: • Location: 100% Remote (United States). Compensation & Benefits: • W2 engagement. Application Instructions: • Interested candidates or referrals can submit their updated resume for consideration.