31 Aug
|
Quess Corp
|
Mumbai
Key ResponsibilitiesData 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 setting 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.QualificationsExperience: 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.Up-to-date 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:
Advanced SQL proficiency and experience with industry-standard data modeling tools (e.g., Erwin, Hackolade, Lucidchart, or SQLDBM).Retail Domain Knowledge:
Strong understanding of retail-specific data domains, including basket analysis, inventory optimization, omni-channel sales, and customer 360.Communication:
Excellent ability to communicate complex technical concepts to non-technical business stakeholders.
📌 Data Modeler (Mumbai)
🏢 Quess Corp
📍 Mumbai