12 of 12 Semantic Layer Jobs in the UK

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 ❯

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 ❯

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 ❯

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 ❯

Be able to work independently as well as within a team Works directly with end-users or a projects team to translate business requirements into technical specifications to drive Semantic layer and report Prioritize technical issue resolution. Requirement gathering & understanding, effort estimation, technical design, project planning and monitoring Understand and analyze the data to find patterns and valuable 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 ❯

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 ❯

of MIT/Kendall Square in Cambridge, MA on a mission to automate the hardest part of data engineering: Our proprietary technology helps in contextualizing data and building the semantic layer that powers BI, analytics, and AI. Agentic data systems are worthless without enterprise context. Our platform is the missing piece for organizations that want their data infrastructure … and building the growth engine that will defi ne our trajectory. You will work closely with the CEO, product, and engineering teams to position our platform as the essential layer for modern data infrastructure. You will work closely with cloud data platform companies such as Snowflake, Databricks, BigQuery and others to drive ekai's platform adoption through key partnerships … fit and customer feedback loops. Establish and manage partnerships with cloud data platforms, analytics vendors, and industry influencers. Brand & Thought Leadership Position the company as a thought leader in semantic layers, data contextualization, and AI-powered analytics. Represent the company at industry events, webinars, and in the media. Team Building Recruit, mentor, and lead a high-performing growth team. 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 ❯

including middleware, APIs, EDI, and event-driven architectures. Experience enabling AI, GenAI, and analytics capabilities through enterprise architecture, including data modeling, governance, and modern platform readiness (e.g., graph databases, semantic layers, AI integration patterns). Excellent communication and influence skills , with a track record of building strong relationships with business and technical stakeholders, and driving architectural decisions that enable 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 ❯

this role is to organize and structure internal and external data assets to support the implementation of AI tools and advanced analytics. This involves creating scalable data models, building semantic layers, and enabling data-driven decision-making across the organization. The role bridges the gap between raw data and actionable insights, ensuring data is effectively modelled and prepared to … this role is to organize and structure internal and external data assets to support the implementation of AI tools and advanced analytics. This involves creating scalable data models, building semantic layers, and enabling data-driven decision-making across the organization. The role bridges the gap between raw data and actionable insights, ensuring data is effectively modelled and prepared to … to your strengths All the responsibilities we'll trust you with: Organise disparate data sources (internal and external) into coherent data models aligned to business needs. Build and maintain semantic layers to simplify data access and enable self-service analytics for business users. Translate business questions into data requirements and ensure data assets meet these needs. Act as a More ❯