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dbt Semantic Model Engineer
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About the Role
We are looking for an experienced dbt MetricFlow and dbt Cloud specialist to design and build a governed semantic layer that enables natural language querying across multiple enterprise data sources hosted in Snowflake.
This is a hands-on delivery role where you will own the semantic layer implementation from architecture through to production deployment, delivering a fully tested and documented solution ready for handover.
Key Responsibilities
- Design and develop dbt MetricFlow semantic models, including entities, dimensions, measures, and business metrics.
- Build ingestion pipelines for multiple external data sources into Snowflake.
- Deploy and manage the semantic layer within dbt Cloud.
- Configure and support the Semantic Layer API.
- Implement role-based access control and integrate metadata management.
- Configure and integrate the dbt MCP server with the deployed semantic layer.
- Develop a lightweight natural language query interface once the semantic layer has been validated.
- Review existing Power BI and Tableau dashboards and migrate business logic into the governed semantic layer.
- Produce clear technical documentation and handover materials.
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Required Skills & Experience
- Strong commercial experience with dbt Core and dbt Cloud.
- Hands-on experience implementing dbt MetricFlow.
- Strong understanding of semantic layer architecture.
- Advanced SQL.
- Extensive Snowflake experience.
- Strong dimensional data modelling skills.
- Experience deploying and managing the dbt Cloud Semantic Layer.
- Experience integrating REST APIs.
- React (or similar front-end framework) experience.
- Experience working with modern data engineering practices and cloud platforms.
- Previous experience working within the pharmaceutical, life sciences, or healthcare industry is essential.
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Desirable Experience
- Migrating Power BI DAX calculations or Tableau calculated fields into a semantic or metrics layer.
- Experience with Snowflake Cortex Analyst or Snowflake Semantic Views.
- Building data ingestion pipelines using REST or XML APIs.
- Experience with metadata management solutions.
- Experience within healthcare, pharmaceutical, or life sciences data environments.
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