Senior Data Architect

Senior Data Modeler/ Semantic Layer Architect Summary

The Senior Data Modeler is responsible for designing, developing, and optimizing data models that power enterprise analytics, reporting, AI/ML initiatives, and data products. This role requires deep expertise in dimensional modeling, semantic layer design, and modern data architecture patterns across batch and streaming paradigms.

The ideal candidate combines strong technical data modeling skills with the ability to translate business requirements into scalable, well-governed data structures. You will partner closely with data engineers, analysts, data scientists, and business stakeholders to ensure data models are performant, maintainable, and aligned with enterprise data strategy.

• Design and implement dimensional models (star and snowflake schemas), Data Vault 2.0 structures, and medallion architecture patterns (Bronze/Silver/Gold) to support enterprise analytics and reporting.
• Build and optimize semantic models using Power BI, dbt Semantic Layer, and other technologies to enable consistent, self‑service analytics across the organization.
• Lead the migration of legacy SSAS tabular models to modern cloud‑based semantic layers while establishing tool‑agnostic metric definitions.
• Design event schemas and data models for streaming architectures, including Kafka topics, CDC pipelines, and schema registries (Avro/Protobuf), ensuring proper schema evolution strategies.
• Partner with data engineers to optimize table designs, partitioning strategies, and materialized views for query performance across cloud platforms (Databricks, Snowflake, Big Query, Azure Synapse).
• Partner with data scientists to design ML‑ready data models and feature stores, supporting feature engineering and training vs. serving patterns.

• Design data models with embedded governance, including ensuring data security at all levels, data lineage documentation, data quality rules, sensitivity classifications (PII/PHI), and business glossary alignment.
• Document and maintain data models, mappings, and business rules within enterprise data catalogs (Alation or similar), ensuring full traceability and impact analysis capabilities.
• Implement slowly changing dimension (SCD) patterns and historical tracking strategies appropriate to business requirements.
• Establish and enforce data modeling standards, naming conventions, and best practices across the data organization.

• Create data products and semantic layers that enable business users to perform self‑service analytics while maintaining governance and data consistency.
• Partner with data scientists to design feature stores and ML‑ready data models, understanding feature engineering requirements and training vs. serving data patterns.

• Serve as a subject matter expert and thought leader for data modeling and semantic layer design, mentoring team members and influencing architecture decisions.
• Contribute to enterprise data strategy by shaping how data products, metrics, and insights are standardized and scaled across the organization.

• Collaborate with stakeholders across business units to gather requirements, translate business needs into data model designs, and recommend solutions for new and existing data products.
• Mentor junior data modelers and data engineers on modeling methodologies, best practices, and modern data architecture patterns.
• Implement data models as code using dbt and version control (Git), establishing CI/CD pipelines for model testing and deployment.
• Ensure operational reliability of data models, address data quality issues promptly, and work with technical and non‑technical users to troubleshoot and resolve data discrepancies.
• Research and recommend new tools, methods, or technologies to continuously improve data modeling practices and data platform capabilities.

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or related field.
• 8+ years of experience in data modeling with demonstrated expertise in enterprise data warehouse and…