76 to 100 of 127 Semantic Layer Jobs in the UK

performance, media ROI, trade effectiveness, sales analytics and category growth.* Advise on modern data foundation principles, including data governance, standardisation, metadata, lineage, quality, interoperability, semantic layers, data products and reuse.* Support the design of scalable data operating models, including ownership, stewardship, governance forums, decision rights and adoption mechanisms.* Bring ...

theory level with no hands-on knowledge.What you will need: Hands-on experience delivering/supporting AI initiatives through Data Management.Core understanding of Ontologies, Semantic Layers, Knowledge Graphs and Context Layers; their differences, use cases and applicability to an organization.Core understanding of Data Agents/Agentic Data Management ...

more important than ever!As Director of Data Products, you will own the platform, the products, the tools, the processes and the self-serve layer, so that the answer arrives before the request does.You will be a force-multiplier for the quality, velocity and impact of Multiverse's decision … senior stakeholders across the org to coordinate a complex set of competing needs.What you'll ownData leverage across MultiverseThe platform, products and self-serve layer that ~800 people use to find, understand and act on our data — reducing the dependency on Data & Insight to answer questions others could answer ...

structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives … agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa ...

with any of the following would be an advantage:SaaS or enterprise data environmentsData integration or ETL processesGit or other version control toolsFamiliarity with semantic layer tools such as Cube or LookMWhy Apply You’ll be joining a highly collaborative team where your work directly influences product quality ...

seeking a Senior BI Developer/Analyst to own data domains end-to-end, from raw data to stakeholder-ready insights. You will design semantic layers and deliver self-serve reporting across delivery, quality, investment, and AI adoption metrics. You will collaborate with engineering leadership, shape metrics, and mentor ...

data sources. You'll have the opportunity to: Design scalable data architecture to support future growth and new data sources. Build intuitive data models, semantic layers, and reporting structures. Improve data quality, accessibility, and governance. Simplify complex data environments through clear documentation and data mapping. Troubleshoot and enhance data ...

hold a team accountable to them.Strong stakeholder management and translation skills, converting business and analytics demand into well-formed requirements.Understanding of data-product thinking, semantic layers and self-service, and how certified products displace tactical reporting.Specialty/London Market business fluency (underwriting, delegated authority, finance, exposure), or the ability ...

configure AI-powered data management capabilities and agentic solutions.Enable AI-ready data by establishing standards for metadata, business glossaries, taxonomies, data products and semantic layers that support both trusted business consumption and AI model interoperability.Collaborate with architecture, engineering and platform teams to design target-state data architectures that enable ...

retail, financial services, healthcare, or telecom. Experience taking clients from AI experimentation to scaled, governed adoption. Familiarity with context engineering concepts: RAG, semantic layers, knowledge bases, MCP. An existing network and reputation in the US data & AI market. Why you should join us We are united by our values ...

DoingAnalytics Engineering and Data ModellingDesign, build, and maintain analytics‐ready data models using dbt, following best practices such as modularity, reusability, and clear semantic layering.Lead the development of greenfield analytics assets, from raw source ingestion through to curated, business‐facing models.Apply strong data modelling techniques, including dimensional modelling, facts … dimensions, and other appropriate design patterns.Own and evolve the analytics layer architecture, ensuring it scales with data volume and business complexity.Ensure data quality and trust through testing, documentation, and observability within dbt.Business PartnershipPartner closely with business stakeholders, analysts, and product teams to understand requirements and translate them into well ...

DoingAnalytics Engineering and Data ModellingDesign, build, and maintain analytics‐ready data models using dbt, following best practices such as modularity, reusability, and clear semantic layering. Lead the development of greenfield analytics assets, from raw source ingestion through to curated, business‐facing models. Apply strong data modelling techniques, including dimensional … modelling, facts and dimensions, and other appropriate design patterns. Own and evolve the analytics layer architecture, ensuring it scales with data volume and business complexity. Ensure data quality and trust through testing, documentation, and observability within dbt. Business PartnershipPartner closely with business stakeholders, analysts, and product teams to understand ...

solutions that drive business outcomes. Responsibilities Build and maintain scalable data pipelines integrating customer, campaign, and operational data into the CDP and marketing data layer Design and manage data models to support segmentation, lifecycle analytics, attribution, and KPI measurement Ensure data quality, consistency, deduplication, and optimisation for analytics … resolution, consent management, and audience readiness Develop event streams and triggers to support customer journey orchestration and real-time decisioning Provide structured datasets and semantic layers for dashboards and advanced analytics Implement data governance practices, including lineage, cataloguing, validation, and GDPR/PII compliance Partner with analytics, MarTech ...

Office and other Divisional Data OfficersCollaborate with SME teams building and scaling data platforms (data lakes, warehouses) across on-prem, cloud, and hybrid environments.Implement semantic layers for consistent, governed data views, enabling self-service analytics and explainable AIOversee data quality processes and enforce standards to minimize data duplication … Experience in building & scaling data lakes, data warehouses, and associated data systems.Databases: SQL, PostgreSQL; MongoDB and cloud-based platforms (e.g. Snowflake, Databricks, Redshift).Semantic Layer: Design and implementation for governed reusable data views.Data Governance Tools: Collibra, Alation, Talend or equivalent.Expertise in ETL tools and processes (e.g., Apache NiFi, Talend ...

gold layers within a Medallion Architecture. Create scalable curated data models using dimensional modelling, star schemas, facts and dimensions, and Kimball methodologies. Define semantic data layers, modelling standards, and governance frameworks to improve consistency, quality, and reusability. Manage logical and physical data models, including metadata, business glossaries, data flows … SKILLS AND EXPERIENCE: Strong hands-on experience in Data Architecture and Data Modelling within enterprise-scale environments. Excellent knowledge of dimensional modelling, star schemas, semantic layers, and Kimball methodologies. Experience designing and implementing curated data models within cloud-based data platforms. Strong understanding of logical, physical, transactional, analytical ...

Define and maintain current and target‐state enterprise data architectures. Develop conceptual, logical, and physical data models. Establish enterprise data domains, canonical models, ontologies, semantic layers, and metadata frameworks. Create data architecture roadmaps aligned to business and digital strategy. Drive data governance, lineage, quality, observability, and master data management … data teams. Essential Skills & Experience Strong enterprise‐level Information or Data Architecture experience. Expertise in data strategy, governance, metadata management, ontologies, knowledge graphs, and semantic modelling. Experience designing end‐to‐end data architectures across complex organisations. Strong Azure data platform experience, including Databricks. Experience delivering large‐scale transformation programmes. ...

Define and maintain current and target-state enterprise data architectures. Develop conceptual, logical, and physical data models. Establish enterprise data domains, canonical models, ontologies, semantic layers, and metadata frameworks. Create data architecture roadmaps aligned to business and digital strategy. Drive data governance, lineage, quality, observability, and master data management … data teams. Essential Skills & Experience Strong enterprise-level Information or Data Architecture experience. Expertise in data strategy, governance, metadata management, ontologies, knowledge graphs, and semantic modelling. Experience designing end-to-end data architectures across complex organisations. Strong Azure data platform experience, including Databricks. Experience delivering large-scale transformation programmes. ...

translation of business requirements into rigorous data structures in collaboration with engineering and domain teams Guide teams on the design and effective use of semantic data models, including their application to agentic AI solutions Semantic & Knowledge Modelling Integrate semantic layers with business glossaries, data catalogues, and lineage … tooling Design and maintain semantic models to support agentic-AI capabilities Help develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and search Define semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data products Guide and control the creation of data domains ...

Senior Software Engineer (Backend/Full-Stack, AI-Native) About Us We're rethinking enterprise integration for developers and AI agents with a semantic layer: describe the data you need, and the platform gets it - fast, deterministic, secure, self-repairing, auditable, scalable. Already live with banks and financial ...

positively impact the education sector.This role sits within the Data & Insights department.Key ResponsibilitiesAct as a subject matter expert for Looker, advocating best practices in semantic modelling, governance, and self-service analyticsDesign, develop, and maintain LookML models, including views, explores, and dashboardsBuild scalable and reusable semantic layers to ensure … processesWhat will you need to succeed Strong experience with Looker and LookML developmentAdvanced SQL skills with several years of hands-on experienceExperience building scalable semantic layers in a BI tool (Looker preferred)Solid understanding of data modelling principles (e.g., star schema, dimensional modelling)Experience with ETL/ELT tools ...

gold layers within a Medallion Architecture. Create scalable curated data models using dimensional modelling, star schemas, facts and dimensions, and Kimball methodologies. Define semantic data layers, modelling standards, and governance frameworks to improve consistency, quality, and reusability. Manage logical and physical data models, including metadata, business glossaries, data flows … SKILLS AND EXPERIENCE: Strong hands-on experience in Data Architecture and Data Modelling within enterprise-scale environments. Excellent knowledge of dimensional modelling, star schemas, semantic layers, and Kimball methodologies. Experience designing and implementing curated data models within cloud-based data platforms. Strong understanding of logical, physical, transactional, analytical ...

framework Creating curated data models using dimensional modelling and Kimball methodologies Defining modelling standards, governance frameworks, and data feed specifications Supporting the design of semantic layers that enable reporting, analytics, and future AI use cases Collaborating closely with Data Engineers and Analytics Engineers in an agile delivery environment Producing … dimensions, and Kimball methodologies Experience designing and implementing Medallion Architecture frameworks Strong knowledge of Azure-based Data Lakehouse environments Experience creating curated and semantic data layers for analytical consumption Proven ability to develop architecture standards, governance frameworks, and modelling best practice Experience working across the full data lifecycle, from ...

enterprise consistency and engineering excellence.Key Responsibilities:1. Enterprise Data Modelling• Lead the enterprise approach to analytical data modelling, including domain models, dimensional models and semantic layers.• Establish reusable modelling patterns and common business entities that create consistency across Data Products.• Reduce duplication and improve the performance, scalability and maintainability … Head of Analytics Engineering to shape the technical roadmap and future engineering capability.Key Technology Areas:Snowflake • DBT • SQL • Python • Git/CI/CD • Semantic Layers • Data Contracts • Data Quality & Observability • Snowflake Cortex • LLMs & AI Agents • AWSSkills & Experience:Must Have• Strong hands-on Analytics Engineering/Data Engineering experience ...

Codify the firm’s unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste’s adoption, from ...

Codify the firm's unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste's adoption, from ...