**Job Description:**
**Role Overview:**
As an experienced Data Modeler at Western Digital's client, you will be responsible for designing and evolving the data architecture and semantic foundation for the enterprise Data Lakehouse platform. You will be translating business requirements into conceptual, logical, and physical models to ensure that data is standardized and business-ready across different layers. Your role will be crucial in implementing canonical data models, enabling consistency across systems and simplifying downstream consumption in various analytics tools. **Key Responsibilities:**
**Data Modeling & Architecture:**
Design conceptual, logical, and physical models supporting ingestion, curation, and consumption. - Define canonical data models at the Silver layer to harmonize data across domains and source systems. - Implement modeling patterns aligned with enterprise standards and optimize physical models for performance. - **Semantic Layer & Business Enablement:**
Build and maintain the semantic layer in tools like Dremio and Power BI. - Provide certified and reusable datasets to BI teams for dashboards and reporting. - Collaborate with business stakeholders to align semantic definitions with canonical data models. - **AI/ML & Conversational Analytics Enablement:**
Prepare feature-ready canonical datasets for ML engineers and data scientists. - Design models for effective consumption by LLM-powered conversational analytics. - Ensure AI/BI queries map back to trusted canonical models. - **Governance, Certification & Metadata:**
Document canonical and semantic models in tools like Atlan and AWS Glue Catalog. - Collaborate with Data Quality Engineers to embed validation and certification rules. - Align canonical modeling with business glossaries, standards, and compliance requirements. - **Collaboration & Best Practices:**
Translate business requirements into canonical and semantic modeling patterns. - Partner with team members to define standards for canonical modeling. - Mentor junior team members on modeling and design principles. **Qualifications Required:**
510 years of experience in data modeling, data architecture, or BI data design. - Strong knowledge of conceptual, logical, physical, and canonical data modeling. - Experience with dimensional modeling, data vault, and semantic modeling. - Hands-on experience with tools like Databricks, Apache Iceberg, AWS services, Dremio, and Power BI. - Proficiency in Power BI modeling, DAX, and dataset certification. - Experience with catalog/governance tools like Atlan. - Cloud certifications: AWS Data Analytics Specialty, Databricks Certified Data Engineer/Architect. **About Uplers:**
At Uplers, our goal is to facilitate the process of finding and applying for relevant contractual onsite opportunities to help talents progress in their careers. We are here to support you through any challenges you may face during the engagement and provide a reliable, simple, and fast hiring experience. Be prepared for a new challenge, a great work environment, and an opportunity to elevate your career by applying today. (Note: More opportunities are available on the portal based on the assessments you clear.) **Job Description:**
**Role Overview:**
As an experienced Data Modeler at Western Digital's client, you will be responsible for designing and evolving the data architecture and semantic foundation for the enterprise Data Lakehouse platform. You will be translating business requirements into conceptual, logical, and physical models to ensure that data is standardized and business-ready across different layers. Your role will be crucial in implementing canonical data models, enabling consistency across systems and simplifying downstream consumption in various analytics tools. **Key Responsibilities:**
**Data Modeling & Architecture:**
Design conceptual, logical, and physical models supporting ingestion, curation, and consumption. - Define canonical data models at the Silver layer to harmonize data across domains and source systems. - Implement modeling patterns aligned with enterprise standards and optimize physical models for performance. - **Semantic Layer & Business Enablement:**
Build and maintain the semantic layer in tools like Dremio and Power BI. - Provide certified and reusable datasets to BI teams for dashboards and reporting. - Collaborate with business stakeholders to align semantic definitions with canonical data models. - **AI/ML & Conversational Analytics Enablement:**
Prepare feature-ready canonical datasets for ML engineers and data scientists. - Design models for effective consumption by LLM-powered conversational analytics. - Ensure AI/BI queries map back to trusted canonical models. - **Governance, Certification & Metadata:**
Document canonical and semantic models in tools like Atlan and AWS Glue Catalog. - Collaborate with Data Quality Engineers
