> Markdown version of [/jobs/ext/4623730-sr-data-modeler](https://www.wearedevelopers.com/jobs/ext/4623730-sr-data-modeler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Modeler - **Company:** Vuori, Inc - **Location:** Carlsbad, CA, United States - **Experience:** Expert - **Salary:** $137,300 - $176,610 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Logic, BigQuery, Information Systems, Databases, Data Governance, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Database Design, Dimensional Modeling, Meta-Data Management, Raw Data, Data Mesh, Sql Optimization, Snowflake, Information Technology, Collibra, Amazon Redshift - **Published:** November 7, 2026 - **Apply:** https://www.careerbuilder.com/job-details/sr-data-modeler-carlsbad-ca--2d7092ff-f6db-4ed0-8a6f-1a7305e3ed07 ## About the Role Data Modeling, Retail, Fitness, Clothes Making, Business Intelligence, Artificial Intelligence (AI), Reporting Dashboards, Database Extract Transform and Load (ETL), Database Design, Data Modeling, Who you are: * 5+ years of experience in data modeling or a related field, including experience operating at a senior or technical lead level * Experience designing or maintaining a semantic layer or metrics layer (e.g., dbt Semantic Layer, LookML, Snowflake semantic views, Cube) that serves multiple downstream consumers * Strong point of view on the difference between a data model and a semantic model, and how to design for both correctness and analyst usability * Advanced SQL skills and deep understanding of relational database design * Experience modeling data within modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) * Experience working with transformation frameworks such as dbt * Strong understanding of data governance, metadata management, and documentation practices * Excellent communication skills, with the ability to translate business needs into technical designs and explain technical concepts to non-technical stakeholders * Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience preferred. * Foundational background in dimensional modeling (Kimball and/or Inmon) - helpful context, though this role emphasizes semantic/metrics layer design over traditional schema work * Experience with data catalog or governance tools (e.g., Collibra, Alation, Atlan) * Familiarity with data mesh or data product concepts * Background in a specific industry domain relevant to the business (e.g., finance, healthcare, retail) ## Description We're looking for a Sr. Data Modeler to design and govern the data models that serve as the foundation for analytics, reporting, and business intelligence across the organization - with particular depth in semantic and metrics-layer modeling. Beyond traditional schema design, you'll build the semantic layer that sits between raw data and downstream consumers (dashboards, reverse-ETL syncs, AI-assisted querying), working closely with data engineers, analysts, and business stakeholders to keep definitions consistent everywhere they're used., * Contribute to the semantic layer strategy - defining metrics, dimensions, and business logic once so they're consistent across BI tools, reverse-ETL syncs, and AI-assisted querying * Design serving-layer models as the "source of truth" for business definitions, resolving ambiguity before it reaches dashboards * Build and govern semantic views/metrics layers (e.g., Snowflake semantic views, dbt metrics/semantic layer) that let analysts and AI tools query curated data without re-deriving business logic * Partner directly with analytics and BI consumers to understand how models get used downstream, and iterate on semantic definitions based on real query patterns * Reduce metric drift by auditing existing reports/dashboards for divergent definitions of the same business concept and consolidating them into governed semantic models