Job Title
Senior Data Modeler - North Star & Semantic Data Modeling / Sr. Data Engineer / Sr. BI Developer – DA&A
Expected Work Experience
8-12 years of hands‑on experience in Data Modeling, Data Warehousing, and SQL.
Job Location
India
Job Summary
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.
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.
- 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.
Other Capabilities
- 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.
Qualifications and Skills
- 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).