Dbt Semantic Model Engineer

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. 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. 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.