1 to 25 of 45 Semantic Layer Jobs in England

their compliance programs.To learn more about Comply, visit comply.comThe Role:We are looking for Senior AI Data Engineers to implement and operationalize Comply's semantic layer — turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This … hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery of semantic layer components, collaborate closely with application and data engineering teams, and ensure that AI-ready data products are reliable, performant, and adopted in practice. ...

9fin.Explain what's moving the numbers. Diagnose spike drivers and build reproducible analysis frameworks rather than one-off dashboards.Own content datasets and the semantic layer. Author dbt models on BigQuery and own the Omni semantic layer so the newsroom gets fast, trustworthy, self-serve answers.Be the embedded … optimisation and reusable datasets.dbt & a cloud data warehouse (BigQuery, Snowflake or similar) — commercial experience building production models, tests and docs.Modern BI with an integrated semantic layer — building self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Engagement and event analytics — designing tracking/instrumentation and analysing ...

production SLA.This is a platform and product leadership role, not an analytics or BI modelling role. Our Analytics team already owns dbt, the semantic layer, and internal BI — you partner with them and consume their definitions; you don't rebuild what they own.What you'll ownIngestion — event-driven … workPeer to the Head of Analytics — you own platform and external data products; they own meaning and internal BI. You consume their semantic layer as a contract, and neither team duplicates the other.Partner with Product Engineering (our Core and Market Vertical domain teams) as your data producers — defining ...

managed data platform across multiple client brands. You'll work across the full data stack, from source connection through to the AI-powered query layer, deploying structured, repeatable data infrastructure that puts business intelligence directly into the hands of brand operators and investors. This is a hands-on technical … role with meaningful client exposure. You won't just build pipelines, you'll encode business logic into a context layer that makes AI genuinely useful on real commercial data. You'll deploy platforms for new brands, maintain and evolve existing ones, and help shape how we productise this capability ...

portfolio companies.Experience with CDC/replication tools feeding a warehouse from an operational database (MySQL, Postgres)Experience with Looker/LookML or another BI semantic layer.Experience in e-commerce, ticketing, or a marketplace business with high-cardinality partner/catalogue data.Experience building or supporting AI/LLM-facing data ...

Event completeness and coverage Cardinality drift Volume anomalies Identity and user stitching integrity Proactively identify and resolve issues before they impact experiments or reporting Semantic Layer Enablement Enable trusted behavioural metrics through: Databricks metric enabled views Power BI semantic models Ensure metrics are usable for: Self serve … data quality Nice to Have Experience supporting experimentation and A/B testing Knowledge of identity resolution and cross device tracking Power BI semantic modelling experience Experience enabling self serve analytics Interest in AI assisted analytics or metric driven agentsAdditional InformationEmployee discount (hello ASOS discount!) Employee sample sales ...

hear from youThe RoleWe are looking for a Payments Data Analyst to join our London team. You will take ownership of the payments data layer, working at the intersection of Product, Commercial, and Engineering to ensure our acquiring business is measurable, scalable, and optimized for performance.You will be responsible … truth" for key payments metrics (volumes, revenue, margins). Collaborate with Engineering to define tracking requirements and proactively identify and resolve data gaps.Semantic Layer Development:Build and maintain a robust semantic layer on top of payments data, ensuring consistent metric definitions across the business and enabling ...

cloud-based Lakehouse platform using Microsoft Fabric Building scalable and reliable data pipelines using a Medallion architecture approach Designing robust data models and semantic layers across multiple business domains Establishing engineering best practices, governance frameworks and development standards Managing and developing a small team of data engineers Partnering with … stakeholders across the organisation to translate business requirements into scalable data solutions Enabling high-quality downstream reporting, analytics and Power BI semantic models Supporting long-term data innovation and AI initiatives across the organisation YOUR SKILLS AND EXPERIENCE: You will bring strong capability in: Strong expertise in dimensional data ...

data models. Author and maintain dbt models, tests and docs that turn raw event streams into reliable, reusable product datasets, and own the Omni semantic layer (topics, metrics, dimensions) so stakeholders trust the numbers.Own instrumentation as a governed product. Design and maintain the event taxonomy, embed a tracking … product analytics tooling. Deep proficiency with Amplitude (or Mixpanel), including designing event taxonomies and conducting behavioural, retention and funnel analysis.Modern BI with an integrated semantic layer. Hands-on experience building intuitive, self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Metric design & governance. Owns single-source ...

present solutions to senior client audiences (pre-sales experience is essential). Translate business requirements into target-state data models, ingestion patterns, and semantic layers. Guide engineers on implementation, performance optimisation, cost control, CI/CD, and operational readiness. Ensure compliance with data governance, privacy, and security controls (RBAC ...

Azure environment. • Hands-on experience working with Databricks, or a strong desire to deepen expertise in it. • Expert understanding of data modelling principles and semantic layer concepts. • Experience working with Azure Data Factory or similar orchestration tools. • Ability to translate business needs into logical, scalable data models. • Comfortable … working across multiple data sources and handling pipeline design. • Experience with Power BI, including semantic models or Tabular Editor. • Curious, collaborative mindset with the ability to push back constructively and guide stakeholders. ...

modelling and data transformation principles. Ability to work effectively within collaborative engineering teams. Desirable Experience: Airflow Databricks Experience supporting AI or machine learning initiatives. Semantic layer experience. Exposure to Azure and multi cloud environments. Understanding of Inmon 3NF data modelling methodologies. Reasonable Adjustments: Respect and equality are core ...

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 ...

intervention for standard use cases.Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration.Define architecture for the semantic layer and self-serve analytics infrastructure.Provide input to data squads for complex data products and support Data Product Managers and Data Engineers where … platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g., SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions).Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions.Provide architectural input to vendor and tooling decisions, evaluating technology ...

cost allocation patternsDesign data ingestion architecture across batch, micro-batch and streaming, with clear boundaries for system to system integrationDefine the architecture for the semantic layer and self-serve analytics infrastructureDefine non-functional standards covering resilience, backup and restore, disaster recovery, observability and operational readinessDefine platform security ...

controlled through to completion. * Manage delivery of the end-to-end reporting pipeline from Salesforce into the Fabric-based data platform (ingestion, modelling/semantic layer alignment, refresh and reporting readiness). * Manage a CRM (e.g., Zoho) to Salesforce data migration including data mapping, cleansing, migration planning, cutover ...

company's enterprise data warehouse. Responsibilities include: Dimensional modelling Star schema design Fact and dimension modelling Slowly changing dimensions Master data management Metadata management Semantic layer design Data lineage Business definitions Data quality controls You will ensure the warehouse becomes the trusted source for all business reporting. Data ...

Claims value chain.Lead the development and expansion of scalable data pipelines supporting both structured and unstructured claims data.Scale and enhance a Claims ontology and semantic layer that connects structured and unstructured data into a unified business knowledge model, improving discoverability, interoperability, and AI readiness.Collaborate with regional Claims leaders … production.Hands-on experience with Databricks, Snowflake, Azure Data Platform, Azure AI Search, Azure Data Lake Storage, and modern cloud architectures.Experience developing enterprise ontologies, semantic layers, or knowledge graph solutions.Experience building Retrieval-Augmented Generation (RAG), AI Search, or document intelligence solutions.Experience scaling enterprise data capabilities across multiple regions and global ...

strategy and influence data governance at scale Involvement in a major cloud migration programme Exposure to emerging areas such as AI-enabled analytics and semantic layer development Clear progression within a structured framework How to Apply If you are an expert in Tableau, apply below ...

technical lead journey.Strong proficiency of SQL and advanced Python is required.Experience with modern data stacks, including dbt, data warehousing (e.g. Snowflake) and visualization/semantic layers like Lightdash or Looker. Ability to understand the underlying business logic of marketing and financials to ensure technical products are meaningful and actionable. ...

delivery focused Data Modeller who combines strong architectural thinking with genuine hands-on capability. You'll be comfortable moving between business requirements, data modelling, semantic layer design and technical implementation, helping to drive a best in class data platform. Key Knowledge Designing and delivering enterprise scale data models … Snowflake Working hands-on across data warehousing, data integration and data exchange solutions Defining and implementing logical and physical data models Developing and optimising semantic layers to support reporting, analytics and self-service consumption Collaborating with Data Architects, Engineers and Business Stakeholders to translate requirements into scalable solutions Supporting ...

configure, test and implement capabilities such as Snowflake Cortex AI, Databricks AI/BI and Mosaic AI capabilities, Microsoft Fabric Copilot, Fabric Data Agents, semantic models, vector search, RAG patterns, AI-assisted data classification and natural language analytics. The role requires someone practical and delivery-focused: able to move …/BI, Genie, Mosaic AI capabilities, Microsoft Fabric Copilot and Fabric Data Agent-style solutions where appropriate. · Ground AI outputs in governed data sources, semantic models, metadata, business definitions and reusable data products. · Support implementation of Retrieval Augmented Generation (RAG), vector search, semantic search and enterprise knowledge retrieval ...

influence technical direction and architectural decisions. Comfortable remaining hands-on while operating in a leadership capacity. Desirable Skills Airflow Databricks AI-focused development experience Semantic layer experience Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have ...

responsibility for the outcome. Strong experience with Databricks and Azure OpenAI, which underpin much of our delivery. Nice to have Ontology, knowledge graph or semantic layer experience. Delivery experience in pharma or CPG. Practical experience designing systems around EU AI Act requirements. Multilingual AI systems in production. ...

analytics solutions. Key Responsibilities Own end-to-end data architecture across Microsoft Fabric Lakehouse, Data Warehouse, Real-Time Intelligence, Data Factory, and Power BI semantic models , ensuring scalability, security, performance, and governance. Act as the Microsoft Fabric subject matter expert , defining standards, reference architectures, accelerators, reusable assets, and delivery … proposals, and present solutions to senior client stakeholders. Pre-sales experience is essential. Translate business requirements into target-state architecture, data models, ingestion frameworks, semantic layers, and enterprise reporting strategies. Guide engineering teams on implementation best practices, performance optimisation, cost management, CI/CD, DevOps, and operational readiness across ...