Senior Data Modeler- North Star Data Model/Snowflake/Source-to-Target

Hi All,

Please share the quality profiles at the earliest.

Role: Senior Data Modeler - North Star Data Model/Snowflake/Source-to-Target (S2T) mappings/SQL

10+ Years of exp

Offshore Any Mastek location
Fulltime

Upo 30 LPA

Senior Data Modeler North Star & Semantic Data Modelling

Experience

10–12 years of hands-on experience in Data Modeling, Data Warehousing, and SQL.

Role Overview

We are looking for an experienced Senior Data Modeler with strong expertise in enterprise data modeling and modern analytical data environments.

The candidate should have a strong understanding of fundamental and advanced data modeling concepts and hands-on experience designing North Star Data Models, source-to-target mappings, and semantic/ontology/context layers that support downstream BI, analytics, and AI use cases.

Key Responsibilities

• Design, develop, and maintain North Star Data Models that provide a consistent and business-oriented representation of enterprise data.
• Develop conceptual, logical, and physical data models based on business and analytical requirements.
• Design normalized and dimensional models, including Star and Snowflake schemas.
• Create detailed source-to-target mappings, including source attributes, target attributes, transformation rules, business logic, and data relationships.
• Translate source-system structures and business requirements into standardized target data models.
• Define business entities, attributes, relationships, keys, hierarchies, measures, and KPIs.
• Design and maintain semantic, ontology, and context layers that provide consistent business meaning across data.
• Ensure the North Star Data Model and semantic layer can effectively support downstream consumption through Power BI, Sigma, and AI/GenAI applications.
• Work closely with data engineers, business analysts, BI teams, and AI teams to ensure the implemented models align with the approved data models.
• Review and enhance existing data models for consistency, scalability, usability, and performance.
• Maintain data-model documentation, data dictionaries, business definitions, and source-to-target mapping specifications.
• Participate in data-model reviews and ensure modeling standards and best practices are followed.

Required Technical Skills

• 8–12 years of Data Modeling experience.
• Strong understanding of:
• Conceptual Data Modeling
• Logical Data Modeling
• Physical Data Modeling
• Dimensional Modeling
• Star and Snowflake schemas
• Normalization and denormalization
• Fact and Dimension modeling
• Slowly Changing Dimensions (SCD)
• Primary and foreign keys
• Hierarchies and relationships
• Business rules and data definitions
• Hands-on experience with North Star Data Modeling or similar enterprise-wide canonical/business data modeling approaches.
• Strong SQL skills, including complex joins, CTEs, window functions, aggregations, and data validation.
• Strong understanding of Snowflake.
• Strong experience creating Source-to-Target (S2T) mappings.
• Understanding of Semantic Layer, Ontology Layer, and Context Layer concepts.
• Understanding of how well-designed data models support BI, analytics, and AI/GenAI consumption.
• Experience with Power BI and/or Sigma is preferred.

Retail Domain Experience – Preferred

Experience working in the Retail domain is highly preferred, with an understanding of areas such as:

• Product and Product Hierarchies
• Customer
• Store and Location
• Sales and Transactions
• Inventory
• Pricing and Promotions
• E-commerce / Digital
• Marketing and Advertising
• Retail Media

Ideal Candidate

The ideal candidate should be able to work across the complete data-modeling lifecycle:

Source Systems Source-to-Target Mapping North Star Data Model Semantic/Ontology/Context Layer Power BI / Sigma / AI Consumption

The person should be strong in data modeling fundamentals as well as advanced modeling techniques, and should be able to understand complex business requirements and convert them into clear, scalable, and business-friendly data models.