7 of 7 Semantic Layer Jobs in the North of England

growing brand runs on. You will own what happens to data once it lands in our data warehouse, including transformation in Dataform, modelling, the semantic layer, and the reporting the business runs on. This is one of two engineering roles we are hiring into the Business Intelligence team. … behind it reflect how the business wants to measure itself, and every metric means one thing. What you will be doing Own the transformation layer in Dataform end to end: the models, dependency graph, tests and documentation between raw BigQuery data and everything the business sees. Build the semantic ...

ownership of our internal reporting tools and partner-facing data products, including OSP Insights. By establishing robust evaluation frameworks and aligning semantic architecture with business outcomes, you will ensure our global partners and internal stakeholders derive maximum value from certified operational data. Key Responsibilities: Define and execute the group … analytics, using Claude and Model Context Protocol (MCP) to enable self-serve access to certified data. Collaborate with Analytics Engineering to shape the unified semantic layer migration onto dbt MetricFlow. Establish evaluation frameworks, telemetry, and logging to rigorously assess AI accuracy, system performance, and metric trust. ...

differentiated career path that is difficult to develop in a purely technology-focused role. Purpose of the roleResponsible for the finance data and ontology layer on which agentic solutions depend. Builds the entities, relationships, definitions, lineage and data contracts sourced from live ERP and EPM systems to a standard … that supports controlled and auditable agent behaviour. The role owns governed finance data products, semantic models and retrieval-ready data services that are secure, permission-aware, observable and suitable for AI, analytics and decision intelligence. ResponsibilitiesBuild and extend the finance ontology covering supplier, invoice, customer, receivable, journal, account, cost ...

real-time data-processing solutions. Lead the design of a Customer Data Platform. Build and evolve a lakehouse architecture using AWS technologies. Create governed semantic models, consistent metrics and clear data definitions. Enable secure, self-service data analysis using modern AI tooling. Automate manual, repetitive or fragile data processes. … open table formats such as Iceberg. Medallion architecture and dimensional data modelling. Strong SQL and Python. SQL Server, SSIS/SSDT and Power BI. Semantic layers, common metrics and data glossaries. Data governance, lineage, retention, classification and auditability. Managing and developing a small technical team. You should also ...

role in developing high-quality, analytics-ready data across its modern data platform. This is an opportunity to take ownership of the curated data layer within a Databricks Lakehouse environment, translating complex business requirements into robust data models and transformation pipelines that support reporting, analytics, and business decision-making. … Responsibilities: Lead the design and development of curated, analytics-ready dimensional and semantic data models. Build, maintain and optimise complex SQL and PySpark transformation pipelines within Databricks. Define and maintain KPI definitions, conformed dimensions and consistent business logic across data domains. Ensure data quality, integrity, testing, observability and performance ...

Management (MDM), Data Quality & Observability, Metadata Management and Data Products as well as supporting organisations adoption of AI including Agentic Data Management, AI Observability, Semantic Layers and Ontologies. We are looking for candidates that have deep experience in one or more core capabilities below and wants … reinventing Data Management & Governance for the AI era. AI Data Management: awareness or experience of areas such as Agentic Data Management, AI Observability, semantic layers, knowledge graphs and ontologies. Data Governance & Strategy : experience supporting the design or implementation of governance frameworks, policies, standards, controls, ownership and stewardship models. Data ...

foundations that make AI delivery faster, safer and easier to scale. Leading design and delivery teams to build AI-ready data foundations, platforms and semantic layers that provide trusted business context, reusable knowledge assets and reliable access to enterprise information for AI and analytics Designing and embedding engineering capabilities … human decision-makers, while supporting technology and platform decisions. Understanding of the foundations required to build trusted enterprise AI, including cloud data platforms, semantic layers, data products, AI evaluation, security, governance and responsible AI practices. Consulting & Client Leadership: Experience in consulting or client-facing roles, building trusted senior client ...