Data Modelling DWH/OLAP

As a Senior Data Modeler for a large, mission-critical analytics platform, you will play a key role in designing, maintaining, and governing enterprise-wide data models. Your responsibilities will include: - Designing and maintaining conceptual, logical, and physical data models using enterprise modeling tools such as Erwin and Mermaid. - Applying Dimensional (Kimball) and Inmon modeling methodologies to support enterprise analytics and reporting. - Translating complex business and analytical requirements into scalable, well-structured data models. - Designing Teradata-optimized models for large data volumes, historical data retention, and performance-intensive workloads. - Establishing and enforcing data modeling standards, naming conventions, and best practices. - Ensuring data integrity, auditability, security, and regulatory compliance. - Participating in data governance activities, including metadata management, data lineage, and data quality. - Collaborating with architects, analysts, and engineering teams to review and validate model implementations. - Creating and maintaining clear data model documentation and mentoring junior modelers. Qualifications & Experience: - Education: B.E. / B.Tech / M.Tech / MCA or equivalent - Experience: 8+ years in enterprise data modeling - Strong experience with Teradata data warehouses - Hands-on exposure to dimensional and enterprise modeling approaches - Experience supporting large analytical platforms; big-data exposure is a plus Primary Skills: - Conceptual, Logical, and Physical Data Modeling - Dimensional (Kimball) and Inmon modeling methodologies - Medallion architecturebased data modeling - Enterprise Modeling Tools: Erwin, Mermaid - Teradata database and warehouse design - Performance-optimized model design for analytics - Data governance, metadata management, and compliance-focused design Secondary Skills: - High-quality data model documentation - Mentorship and knowledge sharing - Strong collaboration with cross-functional teams - Understanding of OLTP and OLAP architectures As a Senior Data Modeler for a large, mission-critical analytics platform, you will play a key role in designing, maintaining, and governing enterprise-wide data models. Your responsibilities will include: - Designing and maintaining conceptual, logical, and physical data models using enterprise modeling tools such as Erwin and Mermaid. - Applying Dimensional (Kimball) and Inmon modeling methodologies to support enterprise analytics and reporting. - Translating complex business and analytical requirements into scalable, well-structured data models. - Designing Teradata-optimized models for large data volumes, historical data retention, and performance-intensive workloads. - Establishing and enforcing data modeling standards, naming conventions, and best practices. - Ensuring data integrity, auditability, security, and regulatory compliance. - Participating in data governance activities, including metadata management, data lineage, and data quality. - Collaborating with architects, analysts, and engineering teams to review and validate model implementations. - Creating and maintaining clear data model documentation and mentoring junior modelers. Qualifications & Experience: - Education: B.E. / B.Tech / M.Tech / MCA or equivalent - Experience: 8+ years in enterprise data modeling - Strong experience with Teradata data warehouses - Hands-on exposure to dimensional and enterprise modeling approaches - Experience supporting large analytical platforms; big-data exposure is a plus Primary Skills: - Conceptual, Logical, and Physical Data Modeling - Dimensional (Kimball) and Inmon modeling methodologies - Medallion architecturebased data modeling - Enterprise Modeling Tools: Erwin, Mermaid - Teradata database and warehouse design - Performance-optimized model design for analytics - Data governance, metadata management, and compliance-focused design Secondary Skills: - High-quality data model documentation - Mentorship and knowledge sharing - Strong collaboration with cross-functional teams - Understanding of OLTP and OLAP architectures