1 to 25 of 45 Semantic Layer Jobs in England

into governed, trustworthy assets and deploy AI systems that meet the reliability standards our institutional clients expect.We operate at the intersection of data engineering, semantic modeling, and applied AI—delivering solutions across the enterprise, spanning the full breadth of Bullish operations from trading floors to treasury, compliance to market … systems that make Bullish’s data not just accessible but intelligible— to business users through conversational analytics, and to AI agents through governed semantic and knowledge layers.The industry is at an inflection point. Google Cloud’s Agentic Data Cloud, BigQuery Graph, Knowledge Catalog, and MCP-native database tooling ...

innovative environments where you can shape the future of data architecture? If so, our client is looking for you! Join us as a Semantic Graph & Ontology Architect and play a pivotal role in developing a Smart Data Fabric that unifies various data sources like Snowflake, SharePoint, and ERP systems … while enhancing AI capabilities through a sophisticated semantic, graph-native foundation. Role: Semantic Graph & Ontology Architect Duration: 6 Months (extension options) Location: Fully Remote Rate: £ Competitive (outside ir35) How You'll Make an Impact: As a hands-on leader, you will: Graph & Semantic Architecture: Design scalable graph ...

innovative environments where you can shape the future of data architecture? If so, our client is looking for you! Join us as a Semantic Graph & Ontology Architect and play a pivotal role in developing a Smart Data Fabric that unifies various data sources like Snowflake, SharePoint, and ERP systems … while enhancing AI capabilities through a sophisticated semantic, graph-native foundation. Role: Semantic Graph & Ontology Architect Duration: 6 Months (extension options) Location: Fully Remote Rate: £ Competitive (outside ir35) How You'll Make an Impact: As a hands-on leader, you will: Graph & Semantic Architecture: Design scalable graph ...

discovery and requirements definition phase. This engagement will focus on end-to-end delivery, including building the data warehouse, developing integration pipelines, creating the semantic layer, and delivering Power BI reporting aligned to established architecture and design. The source system is a mission-critical, always-on, globally connected … core system, ensuring efficiency across global time zones and 24/7 operations Build Power BI tabular models and datasets to form the semantic layer, including robust row-level security (RLS) Deliver: Layer 1: Standard operational and management reporting Layer 2: OLAP-style analytical capabilities ...

discovery and requirements definition phase. This engagement will focus on end-to-end delivery, including building the data warehouse, developing integration pipelines, creating the semantic layer, and delivering Power BI reporting aligned to established architecture and design. The source system is a mission-critical, always-on, globally connected … core system, ensuring efficiency across global time zones and 24/7 operations Build Power BI tabular models and datasets to form the semantic layer, including robust row-level security (RLS) Deliver: Layer 1 : Standard operational and management reporting Layer 2 : OLAP-style analytical capabilities ...

iterate on autonomous and semi-autonomous agent workflows that retrieve, reason over, and act on enterprise data (with guidance on architecture and safety). Semantic Layers & Ontologies - Contribute to semantic models (metrics, definitions, and metadata) that make it easier for business users to query data consistently. LLM-Powered … explain complex technical concepts to non-technical stakeholders. What Would Make You Stand Out: Experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel). Exposure to semantic layer technologies (e.g., dbt metrics layer, Cube, AtScale) or knowledge graph tooling. Familiarity with BI platforms ...

analytics platforms utilizing: SAP Business Data Cloud (BDC) for unified data ecosystems and business context integration. SAP Datasphere for data modeling, federation, virtualization, and semantic layer development. SAP Analytics Cloud (SAC) for reporting, dashboards, planning, and predictive analytics. SAP BDC Connect and Data Products frameworks. Intelligent Applications … Data Packages. Medallion Architecture patterns leveraging SAP HANA Cloud. AI-enabled analytics and data-driven decision support. Key responsibilities include: Designing analytical, semantic, and business-layer data models aligned with organizational KPIs and reporting requirements. Defining data integration strategies across SAP and non‐SAP environments, including real‐time ...

data products they need Contribute to data governance, cataloguing, access management and platform security (Analytics Engineer) Sit closer to the analyst side—transformation, modelling, semantic layer, metrics (Platform Engineer) Sit closer to the platform side—infra, tooling, developer experience for data practitioners (For Senior/Lead/Principal ...

data products they need Contribute to data governance, cataloguing, access management and platform security (Analytics Engineer) Sit closer to the analyst side—transformation, modelling, semantic layer, metrics (Platform Engineer) Sit closer to the platform side—infra, tooling, developer experience for data practitioners (For Senior/Lead/Principal ...

team of data engineers (minimum 2) Work closely with stakeholders to translate business requirements into scalable data solutions Enable downstream analytics, including Power BI semantic models and dashboards Contribute to long-term AI and data innovation initiatives YOUR SKILLS AND EXPERIENCE: 6+ years' experience in data engineering Strong expertise … data modelling (dimensional modelling and semantic layer design) Hands-on experience with Microsoft Fabric and/or Azure data services Proven end-to-end delivery across the data lifecycle (through to visualisation) Experience managing or mentoring engineers Strong stakeholder engagement and communication skills Nice to have: Experience working ...

trusted datasets and metrics that power workflows, internal tools, and customer-facing insights. Enable self-service analytics by establishing clear data contracts, documentation, and semantic layers. Build use cases including, but not limited to: Capacity planning Cost optimisation Reliability analysis Customer reporting Collaborate with Product and Commercial teams ...

Snowflake Develop reusable data assets for downstream reporting and analytics Troubleshoot and resolve data quality or performance issues Improve the Reporting & Analytics Layer Design a clean, scalable semantic layer for reporting Standardise key business metrics and definitions Support transition away from legacy report-first design toward model ...

engineers across squads Ensure alignment and compliance with data platform usage (warehousing, orchestration, transformation ways of working) Drive consistency in data modeling approaches and semantic layers for analytics products Champion data quality, observability, and governance practices Cross-Squad Alignment & Delivery Enablement Partner with product managers and tech leads ...

growth. What the role involves: Designing and building cloud-native data infrastructure that scales Building and maintaining reliable ingestion, transformation and orchestration pipelines Developing semantic models and governed data structures that people can trust Improving data quality, observability and lineage across the platform Contributing to architectural decisions and long … with AWS and modern warehousing tech - Redshift in particular Experience with dbt or similar transformation tooling A good understanding of data modelling, governance and semantic layer design Experience with agentic AI or AI-assisted tooling within data workflows Strong engineering judgement and the ability to balance long term ...

modelling standards, including dimensional modelling approaches. Develop CI and CD pipelines to enable reliable deployment and testing of data products. Create and maintain a semantic layer for self-service analytics and reporting. Partner with stakeholders across multiple business areas to translate data needs into solutions. Deliver insights … data pipelines using Spark and Python or SQL. Strong understanding of data modelling, including star and snowflake schemas. Experience working with BI tools and semantic layers such as Looker or similar platforms. Familiarity with version control and CI or CD workflows. Ability to communicate complex technical concepts ...

modelling standards, including dimensional modelling approaches. Develop CI and CD pipelines to enable reliable deployment and testing of data products. Create and maintain a semantic layer for self-service analytics and reporting. Partner with stakeholders across multiple business areas to translate data needs into solutions. Deliver insights … data pipelines using Spark and Python or SQL. Strong understanding of data modelling, including star and snowflake schemas. Experience working with BI tools and semantic layers such as Looker or similar platforms. Familiarity with version control and CI or CD workflows. Ability to communicate complex technical concepts ...

modelling standards, including dimensional modelling approaches. Develop CI and CD pipelines to enable reliable deployment and testing of data products. Create and maintain a semantic layer for self-service analytics and reporting. Partner with stakeholders across multiple business areas to translate data needs into solutions. Deliver insights … data pipelines using Spark and Python or SQL. Strong understanding of data modelling, including star and snowflake schemas. Experience working with BI tools and semantic layers such as Looker or similar platforms. Familiarity with version control and CI or CD workflows. Ability to communicate complex technical concepts ...

trusted partner to senior leaders, influencing at executive level. Experience defining and embedding end‐to‐end BI delivery methodologies. Strong understanding of data governance, semantic models and trusted data principles. Hands‐on experience delivering BI in an agile, iterative environment. Experience working within insurance or wider financial services data … reporting estates. Exposure to AI‐augmented analytics or automated insight generation. Experience leading BI teams through organisational change or consolidation. Familiarity with enterprise semantic layer technologies. Responsible Artificial Intelligence usage. What We Will Offer You Recognised and rewarded for a job well done, we have a range ...

Foundry, covering data integration, pipelines, transformations, ontology modelling, governance, and operational applications Own and evolve the enterprise ontology , defining object types, links, actions, and semantic relationships across clinical and operational domains Design scalable, modular, and governed data pipelines , following Foundry best practices (DRY principles, no circular dependencies) Integrate structured … Strong understanding of healthcare datasets , including: EPR/PAS FHIR/HL7 Clinical coding and workforce data Proven experience in: Enterprise data modelling/semantic layer/ontology design Delivering within regulated environments (NHS, ICS, Government, or large healthcare providers) Strong stakeholder management and communication skills , with ...

scaling of CIFF’s operations and collective intelligence (through data visualisation and similar platforms. Support the Enterprise Architect in modernising the BI ecosystem (e.g., semantic layer and self‐service BI) and deliver real‐time impact dashboards, programme scorecards, and portfolio insights. Work with missions, programme teams to embed ...

Engineer positions—for upcoming roles across commercial, customer, product, finance, marketing and operations reporting. These are hands-on roles where you'll own the layer that turns warehouse data into the dashboards, semantic models and self-service tools the business actually uses to make decisions. You'll work … translate them into BI deliverables Design and build production-grade dashboards and reports in Power BI, Tableau, Looker or equivalent Develop and maintain semantic models (DAX, LookML, Tableau data models) that scale across the organisation Build and optimise data marts and reporting layers in the warehouse Write efficient ...

Engineer positions—for upcoming roles across commercial, customer, product, finance, marketing and operations reporting. These are hands-on roles where you'll own the layer that turns warehouse data into the dashboards, semantic models and self-service tools the business actually uses to make decisions. You'll work … translate them into BI deliverables Design and build production-grade dashboards and reports in Power BI, Tableau, Looker or equivalent Develop and maintain semantic models (DAX, LookML, Tableau data models) that scale across the organisation Build and optimise data marts and reporting layers in the warehouse Write efficient ...

Business to ensure analytics is embedded in every decision Drive "Data as a Product" , owning the evolution of our data models and semantic layer, ensuring teams can reliably self‐serve from high‐quality data products Champion governance and guardrails , establishing rigorous standards for modelling, semantics, testing, and auditability ...

cloud (GCP, BigQuery, Looker data lake). These standards will include BiqQuery Layout - naming standards, key consistency, suffix standards, data set layering etc Looker Semantic Layer - user view definitions, dimensions grouping, aggregation definitions, hidden join management MetaData and Documentation - Looker and BQ field description standards Schema Design standards … flattened views, deterministic types, order consistency, semantic description, enum constraints etc Partitioning and clustering standards Policy Tags Star Schema Design standards Our client will also need to understand how to implement these standards as code and how they monitor adherence as their data engineering supplier builds the data products. ...

Azure Environment. Key Criteria: Strong knowledge of: Cloud-native data platforms (e.g., lakehouse, warehouse, streaming systems) Modelling approaches (medallion, dimensional, event-driven, semantic layers) Data governance frameworks and metadata tooling Data lineage, cataloguing, discovery, and documentation Data quality and observability tooling Data access/security patterns Skilled in standardisationcreating ...