11 of 11 Semantic Layer Jobs in the City of London

turns customer goals into technical valid, commercially credible designs covering: Data Ingestion and Integration Storage and management Processing and Transformation Design of the Semantic Layer Data Sharing Delivery of AI-ready data Governance, security, observability and cost are designed in at every stage. They work closely with Solution …/ELT, transformation and orchestration approaches suited to the customer's scale, skills and operating model. Data Storage & Management - Design the logical storage layer, including open table formats, database selection, partitioning, retention and lifecycle management. Work with Hybrid Platforms architects, who own physical storage and infrastructure. Data Governance, Discovery ...

ways of working and ownership. Build AI-ready data and use AI in engineering Work with Data Product, Analytics and AI teams to implement semantic models, ensuring business definitions and relationships are consistently represented in the engineered data products. Use AI-assisted tools across the engineering lifecycle, from code … platform architecture, including medallion and lakehouse patterns, ELT and dimensional or domain data modelling. Experience delivering data products end to end, including contributing to semantic layer implementation for analytics and AI use. Practical experience embedding data catalogue, data quality, lineage and data observability tooling into engineering delivery. Good ...

quality and lineage practices. Build AI-ready data and bring AI into data engineering: partner with Data Product, Analytics and AI teams to implement semantic models, ensuring business definitions and relationships are consistently represented in the engineered data products. Apply AI across data engineering, from data quality monitoring … platform architecture, including medallion and lakehouse patterns, ELT and dimensional or domain data modelling. A track record of designing and delivering data products, including semantic layer implementation for AI and analytics use. Practical experience embedding data governance tooling into delivery, covering data catalogue, data quality, lineage and data ...

credentials and adjacent platform experience will be considered. The Work Architecture & Design Design and document multi-agent architecture blueprints, agentic orchestration patterns, knowledge and semantic layer blueprints, AI governance blueprints, and AgentOps/LLMOps architecture Design the knowledge architecture underpinning agent intelligence: embeddings pipelines, vector retrieval, and semantic search — structured around commerce-specific intent, product relationships, and category hierarchies Architect the integration layer connecting agentic systems to enterprise commerce stacks (OMS, PIM, DAM, CRM, payments, pricing, fulfilment) via API gateways, event buses, and emerging agentic protocols (MCP, A2A, ACP, UCP) Lead build vs. buy decisions across ...

platforms (e.g. Snowflake), with the ability to engage effectively with technical teams. Hands‐on experience with technical tooling and code development experience. Knowledge of semantic layers, graphs, and ontologies. Experience and curiosity around AI‐powered development. Ability to translate business needs into clear data design, with a focus ...

Make sure AI runs in a safe, governed environment, with our data in the best possible shape (access, privacy and responsible use) Own the semantic layer as the single place we define our metrics, used by our BI tool, Claude and every agent we build Build in evals ...

would struggle to find anywhere else in this industry. You will sit between data engineering and the business. That means turning commercial questions into semantic models, curated datasets and reusable data assets that leaders across EMEA and APAC rely on, working with our engineers on the upstream design that … would struggle to find anywhere else in this industry. You will sit between data engineering and the business. That means turning commercial questions into semantic models, curated datasets and reusable data assets that leaders across EMEA and APAC rely on, working with our engineers on the upstream design that ...

strategies, investment cases, roadmaps and measurable business outcomes. Lead teams of consultants, engineers and architects. Provide technical direction across data platforms, AI, GenAI, semantic architectures and agentic solutions. Ensure AI solutions are secure, governed, reliable and suitable for production. Navigate Financial Services regulatory and risk requirements. Lead proposals, RFPs … business development and selling work. Experience engaging senior stakeholders and presenting at governance/board level. Desirable Experience with Databricks, Azure, AWS, GCP, Snowflake, semantic layers, data products, agentic AI architectures and responsible AI in production would be highly beneficial. This is an opportunity for a senior Data ...

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 … Data Management & Governance for the AI era. Core capabilities 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. ...

operate across the front, middle and back office. Key Responsibilities Design and build advanced AI solutions, including agentic AI, RAG, GraphRAG, knowledge graphs and semantic layers. Explore emerging technologies and rapidly test where they could create business value. Build prototypes and experiments with production scalability, maintainability and integration … software development. Experience building with LLMs, agents, RAG and modern AI frameworks. Strong understanding of knowledge graphs, large-scale graph technologies, GraphQL and semantic modelling. Experience taking experimental technologies beyond prototypes towards scalable production solutions. Good understanding of APIs, cloud platforms and enterprise integration. Some understanding of data engineering ...

chemical markets get intelligence, and this role owns the platform foundations that make it possible. You will define the AI-ready data strategy, semantics layer, and MCP-first distribution approach that powers internal product teams, partner integrations, and AI-native customer experiences. This is a highly influential individual contributor … stakeholders to accelerate adoption, integrations, and commercial opportunities Requirements A track record shipping platform capabilities that others build upon, such as APIs, data products, semantic layers, evaluation frameworks, or comparable platform primitives Experience owning platform strategy, roadmap, and delivery outcomes in data, AI, developer platform, or similarly technical product ...