Senior Data Modeler – North Star & Semantic Data Modeling / Sr. Data Engineer / Sr. BI Developer – DA&A

8–12 years of hands-on experience in Data Modeling, Data Warehousing, and SQL.

India

We are looking for an experienced Senior Data Modeler / Sr. Data Engineer / Sr. BI Developer with strong expertise in enterprise data modeling and modern analytical data environments, focused on Data Automation & AI and Data Engineering – Data Analytics – Databricks (Technical). 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/GenAI use cases. Candidate must have relevant experience of 8–12 years.

• 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.
• Collaborate with Data Engineering – Data Analytics – Databricks teams to implement data models in modern data platforms and pipelines.
• Support data automation initiatives and AI/GenAI use cases by ensuring data models are optimized for analytical and machine learning workloads.
• 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.

• Ability to understand complex business requirements and convert them into clear, scalable, and business-friendly data models.
• Strong collaboration skills to work with cross-functional teams including data engineers, BI developers, AI/ML teams, and business stakeholders.
• Strong problem-solving and analytical skills with attention to data quality, consistency, and performance.
• Ability to operate in retail-focused analytical environments and adapt models to evolving business needs.
• Capability to contribute to Data Automation & AI initiatives and support advanced analytics and GenAI solutions.
• Strong documentation and communication skills to articulate data modeling decisions and standards.

• 8–12 years of Data Modeling experience, with hands-on work in Data Warehousing and SQL.
• 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 and its use in modern analytical data platforms.
• 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.
• Experience working in the Retail domain is highly preferred, with understanding of:
  – Product and Product Hierarchies
  – Customer
  – Store and Location
  – Sales and Transactions
  – Inventory
  – Pricing and Promotions
  – E-commerce / Digital
  – Marketing and Advertising
  – Retail Media
• Experience in Data Engineering – Data Analytics – Databricks (Technical) environments.
• Exposure to Data Automation & AI initiatives and modern data and analytics architectures.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Analytics, or a related field (or equivalent experience).