15 of 15 Semantic Layer Jobs in the UK

you'll make a lasting impact on how data empowers the organisation. THE ROLE You'll join the data team to lead the design and delivery of a new semantic layer in Looker. You'll work with stakeholders across departments to translate business needs into performant, trusted data models using LookML and dbt. You'll also play a … and Snowflake Supporting a stakeholder-first approach to data usability and access. KEY SKILLS AND REQUIREMENTS Extensive experience operating within Snowflake environments Advanced experience with Looker and LookML, including semantic layer modeling and dashboard design. Proficiency in SQL and dbt, with a strong understanding of data modeling best practices. Strong communication skills with the ability to translate complex More ❯

across the organisation. Key Responsibilities Build and maintain scalable data pipelines using Azure Data Factory and Databricks Develop transformation workflows in dbt, SQL, and Python Design dimensional models and semantic layers to support analytics use cases Implement automated data quality checks, monitoring, and alerting systems Create reusable data assets and documentation to support self-serve analytics via Power BI More ❯

and self-service capabilities by default. As an ETL Developer, develop, test and/or quality assure extracts of data from corporate systems into the Data Lake As a Semantic Layer Developer, develop, test and/or quality assure semantic models As a Report Developer, develop, test and/or quality assure reports, visualisations and dashboards, producing More ❯

self-serve capabilities, and strategic decision-making across the business. You will collaborate with our Data Manager, Data Engineer, Analysts, and business stakeholders, building the scalable data pipelines and semantic layers that power our reporting, dashboards, and critical decisions. This is a remote, UK based role and the hours of work are 37.5 hours per week. The salary range … deep understanding of ETL/ELT processes and tools (e.g., Fivetran, Airbyte, Stitch). Experience with data visualisation tools (e.g., Mode, Looker, Tableau, Power BI) and designing robust BI semantic layers. Exceptional understanding of data warehousing principles, dimensional modeling, and analytics best practices. Proficiency in Git-based workflows with a strong background in implementing and managing CI/CD More ❯

design decisions, and metric calculations. Keep data dictionaries and documentation up to date. Quality Assurance – Support UAT for migrated reports, validating both data accuracy and alignment with business requirements. Semantic Layer Alignment – Map legacy Power BI models into a centralised, cloud-based semantic layer. Reporting Optimisation – Rationalise and enhance existing BI products to improve adoption, performance, and … Proven Migration Experience – Direct experience in migrating reporting/BI assets from on-premise to cloud (ideally Azure/Fabric). BI & Data Modelling Skills – Familiarity with Power BI, semantic models, star schemas, and data warehouse design principles. Documentation Excellence – A passion for producing high-quality documentation with exceptional attention to detail. Technical Acumen – Ability to critique BI schema More ❯

design decisions, and metric calculations. Keep data dictionaries and documentation up to date. Quality Assurance – Support UAT for migrated reports, validating both data accuracy and alignment with business requirements. Semantic Layer Alignment – Map legacy Power BI models into a centralised, cloud-based semantic layer. Reporting Optimisation – Rationalise and enhance existing BI products to improve adoption, performance, and … Proven Migration Experience – Direct experience in migrating reporting/BI assets from on-premise to cloud (ideally Azure/Fabric). BI & Data Modelling Skills – Familiarity with Power BI, semantic models, star schemas, and data warehouse design principles. Documentation Excellence – A passion for producing high-quality documentation with exceptional attention to detail. Technical Acumen – Ability to critique BI schema More ❯

design decisions, and metric calculations. Keep data dictionaries and documentation up to date. Quality Assurance – Support UAT for migrated reports, validating both data accuracy and alignment with business requirements. Semantic Layer Alignment – Map legacy Power BI models into a centralised, cloud-based semantic layer. Reporting Optimisation – Rationalise and enhance existing BI products to improve adoption, performance, and … Proven Migration Experience – Direct experience in migrating reporting/BI assets from on-premise to cloud (ideally Azure/Fabric). BI & Data Modelling Skills – Familiarity with Power BI, semantic models, star schemas, and data warehouse design principles. Documentation Excellence – A passion for producing high-quality documentation with exceptional attention to detail. Technical Acumen – Ability to critique BI schema More ❯

financial metrics and reporting. Experience with database management and cloud platforms (e.g., Snowflake). Excellent communication and stakeholder management skills. Understanding of Agile methodologies. Nice to Have Experience with semantic layer tools and SSRS. Knowledge of Azure DevOps. Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we More ❯

can be used for effective analysis and decision-making. Partner with subject matter experts to understand the logic and relationships between data objects and build physical data models and semantic layers which reflect those needs. Provide support to colleagues and users, investigate issues and present findings to technical and non-technical stakeholders Collaborate with the Data Engineering and Operations More ❯

can be used for effective analysis and decision-making. Partner with subject matter experts to understand the logic and relationships between data objects and build physical data models and semantic layers which reflect those needs. Provide support to colleagues and users, investigate issues and present findings to technical and non-technical stakeholders Collaborate with the Data Engineering and Operations More ❯

processes is also important for success in this role. Key Responsibilities Architect and manage enterprise data solutions in SAP Analytics Cloud (SAC). Design and implement data models and semantic layers to support operational and strategic analytics. Lead integration of data from SAP (e.g., S/4HANA, BW/4HANA) and external platforms using cloud and API technologies. Oversee More ❯

data enrichment. Data Modeling for AI Workflows • Architect and maintain data models optimized for AI usage-structured for quick access by LLMs, retrieval engines, and embedded reasoning tools. • Integrate semantic layers and metadata mapping to facilitate natural language querying and low-code data exploration. Documentation, Scaling & Knowledge Ops • Document all AI workflows-from prompt structures and agent behaviors to More ❯

BigQuery architecture, optimization, and cost management Advanced SQL skills and production-level experience using dbt (or similar tools) to build modular, testable transformation pipelines Practical mastery of LookML and semantic layer design within Looker, including Explores, joins, derived tables, and scalability best practices It will also help you to have Experience establishing and enforcing data governance standards through More ❯

SAP HANA, and the SAP Cloud Platform Solid experience in cloud-based analytics architecture and integration of hybrid data sources (SAP and non-SAP) Strong understanding of ETL processes, semantic layers, data validation, and transformation logic within SAC Duration: 6 months (View for Extension) Salary: Up to £575 per day (Inside IR35 More ❯

class technology powerhouse? Apply now! Responsibilities: Manage, and maintain the enterprise data architecture within SAP Datasphere, ensuring scalability, security, and performance Implement advanced data models using spaces, views, and semantic layers to support operational and analytical use cases Integrate data from SAP (eg, S/4HANA, BW/4HANA) and non-SAP sources (eg, APIs, cloud platforms) to enable … within SAP Datasphere Requirements: Hands-on experience designing, implementing, and optimizing solutions in SAP Datasphere (formerly SAP Data Warehouse Cloud) Proficiency in building complex data models using spaces, views, semantic layers, and graphical modeling tools Deep understanding of integrating SAP (S/4HANA, BW/4HANA) and non-SAP sources (cloud platforms, APIs, flat files) into Datasphere Experience in More ❯