Job Description

Key Responsibilities
- Data Architecture & Modeling: Design, develop, and maintain conceptual, logical, and physical data models tailored to the complexities of the retail industry (e.g., point-of-sale, inventory management, customer lifecycle, and e-commerce data).
- Dimensional Modeling (Kimball): Apply strict Kimball Concepts and methodologies to design robust star and snowflake schemas that support high-performing BI and reporting solutions.
- Medallion Architecture Implementation: Architect data flows utilizing the Medallion Architecture (Bronze, Silver, Gold layers) within our data lake/lakehouse environment to progressively refine and enrich raw data into business-ready assets.
- Semantic Layer Design: Design and govern a unified Semantic Layer to bridge the gap between complex data structures and business users. Ensure consistent business definitions, metrics, and dimensions across all BI platforms (e.g., Power BI, Tableau, Looker).
- Collaboration & Translation: Partner closely with data engineers, product managers,



and retail business stakeholders (merchandising, supply chain, marketing) to translate complex business requirements into scalable data structures.
- Data Governance & Quality: Establish data modeling standards, maintain comprehensive data dictionaries, and ensure data integrity and compliance across all data products.

Qualifications
- Experience: 5+ years of dedicated experience in data modeling and data architecture, specifically within the Retail or FMCG industry.
- Methodology Mastery: Deep, demonstrable expertise in Dimensional Modeling and the Kimball lifecycle.
- Contemporary Data Architecture: Proven experience designing data models for cloud data warehouses/lakehouses (e.g., Snowflake, Databricks, BigQuery) utilizing the Medallion Architecture.
- Semantic Layer Expertise: Hands-on experience designing and implementing semantic layers or metrics layers (using tools like dbt, LookerML, AtScale, or SSAS).
- Technical Skills: Ad

📌 Data Modeler (India)
🏢 Quess Corp
📍 India