BigQuery, dbt), ensuring they are scalable, maintainable, and effectively serve the complex analytical and operational needs of the entire organisation. You will be instrumental in defining and refining the semanticlayer (Cube) to guarantee consistent and accurate metrics. Drive Data Integration and Transformation Excellence: Establishing and enforcing best practices for data ingestion and transformation processes, collaborating closely with … understanding of methodologies and significant hands-on experience using dbt, complemented by practical experience with orchestration tools such as Dagster or Airflow. Have a proven track record of successful semanticlayer implementation, showcasing experience in the end-to-end implementation and management of a modern semanticlayer (e.g., Cube) to empower consistent and performant self-service More ❯
toward a clearer separation between Data Engineering, Analytics Engineering, and Data Product disciplines. This role will sit firmly in the Analytics Engineering function, focused on modelling and building the semanticlayer that powers consistent, reliable insights across the company’s BI and data science platforms. This role will focus on the “middle layer", designing dimensional models, building … reusable dbt pipelines, and ensuring the semanticlayer meets the needs of Power BI, Looker, and data science teams. There’s also the opportunity to stretch into data product work, partnering with stakeholders to understand and translate business requirements into robust data models. Key Responsibilities: Build and maintain well-structured, scalable data models using dbt and Kimball/… Medallion architecture. Develop and own the semanticlayer, shifting calculations and business logic out of BI tools and into the model layer to drive consistency across Looker, Power BI, and other downstream consumers. Work closely with Data Engineers responsible for ingestion (from source systems to raw layers such as S3 or cloud storage), but focus your efforts More ❯
toward a clearer separation between Data Engineering, Analytics Engineering, and Data Product disciplines. This role will sit firmly in the Analytics Engineering function, focused on modelling and building the semanticlayer that powers consistent, reliable insights across the company’s BI and data science platforms. This role will focus on the “middle layer", designing dimensional models, building … reusable dbt pipelines, and ensuring the semanticlayer meets the needs of Power BI, Looker, and data science teams. There’s also the opportunity to stretch into data product work, partnering with stakeholders to understand and translate business requirements into robust data models. Key Responsibilities: Build and maintain well-structured, scalable data models using dbt and Kimball/… Medallion architecture. Develop and own the semanticlayer, shifting calculations and business logic out of BI tools and into the model layer to drive consistency across Looker, Power BI, and other downstream consumers. Work closely with Data Engineers responsible for ingestion (from source systems to raw layers such as S3 or cloud storage), but focus your efforts More ❯
toward a clearer separation between Data Engineering, Analytics Engineering, and Data Product disciplines. This role will sit firmly in the Analytics Engineering function, focused on modelling and building the semanticlayer that powers consistent, reliable insights across the company’s BI and data science platforms. This role will focus on the “middle layer", designing dimensional models, building … reusable dbt pipelines, and ensuring the semanticlayer meets the needs of Power BI, Looker, and data science teams. There’s also the opportunity to stretch into data product work, partnering with stakeholders to understand and translate business requirements into robust data models. Key Responsibilities: Build and maintain well-structured, scalable data models using dbt and Kimball/… Medallion architecture. Develop and own the semanticlayer, shifting calculations and business logic out of BI tools and into the model layer to drive consistency across Looker, Power BI, and other downstream consumers. Work closely with Data Engineers responsible for ingestion (from source systems to raw layers such as S3 or cloud storage), but focus your efforts More ❯
ownership and advancement. Opportunity to work with cutting-edge tools. We have a modern data stack and are leaning into AI tools like Cursor and pursuing new techniques like semantic layers that accelerate our productivity and impact. THE UPSIDE Equity: Have a stake in the business that you're helping to build and grow. Work remotely: Live and work More ❯
