101 to 125 of 127 Semantic Layer Jobs in the UK

consultancies. This is an opportunity to join a highly respected consultancy focused exclusively on the modern data stack, helping organisations build scalable analytics platforms, semantic layers, governed self-service reporting, and AI-enabled analytics solutions using Google Cloud technologies. Unlike larger consultancies, you'll work directly with clients, company … rather than simply delivering technical tasks. What you'll be doing Client Delivery Design and implement modern analytics platforms Build scalable data models and semantic layers Develop reporting and analytics solutions Deliver multiple concurrent consulting engagements Lead technical discussions directly with clients Consulting & Stakeholder Management Run discovery workshops ...

service model that serves Risk and Compliance. Delivery. Deliver priority data products and automation. Operating disciplines. Own the data‐product operating disciplines, product management, semantic and taxonomy ownership, and AI access and insight assurance. Outcomes. Measure and report success by decision‐influence and accountability outcomes, not build volume. … Work With LLMs and agentic frameworks RAG architectures AI agents and orchestration (e.g. LangChain/LangGraph) Python and modern data engineering Snowflake and governed semantic layers AWS/GCP cloud services Vector databases Data pipelines and MLOps tooling Business intelligence and visualisation tools #LI-AB3 What ...

translation of business requirements into rigorous data structures in collaboration with engineering and domain teamsGuide teams on the design and effective use of semantic data models, including their application to agentic AI solutionsSemantic & Knowledge ModellingIntegrate semantic layers with business glossaries, data catalogues, and lineage toolingDesign and maintain semantic models to support agentic-AI capabilitiesHelp develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and searchDefine semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data productsGuide and control the creation of data domains that align with the banks underlying capabilitiesData Engineering ...

Staff Analytics Platform Engineer, you’ll provide technical leadership across the entire analytics platform, from ingestion and transformation tooling to Snowflake architecture, semantic modelling, and secure analytics environments. You’ll define the patterns, standards, and infrastructure that enable analysts, data scientists, and product teams to build reliable, scalable analytics … with you. What you’ll be doing Co‐owning the analytics platform architecture, designing end‐to‐end solutions across Snowflake, ingestion pipelines, dbt infrastructure, semantic layers, and secure analytics environments. Defining and driving the long‐term technical vision for the analytics platform, ensuring it is scalable, cost‐efficient, secure ...

within the CDPJourney Orchestration Data Readiness: Enable event streams, triggers, and monitoring to support accurate, timely customer journeysAnalytics & Dashboarding Enablement: Provide structured datasets and semantic layers for reporting and dashboards, aligned with KPI frameworksData Governance & Quality Assurance: Maintain data quality, lineage, and compliance with GDPR and PII standardsCollaboration & Strategic … across digital, CRM, transactional, and behavioural data; support identity resolution, consent handling, audience activation, journey events, trigger logic, and behavioural signalsBuild data marts and semantic layers for dashboarding and BI tools such as Power BI or Tableau; structure datasets optimised for KPI frameworks, attribution, funnel, and lifecycle analyticsApply data ...

evolving fast. With new tooling changing how we work, we are shifting from building data pipelines to building AI first data products, developing rich semantic and data context layers and empowering self-serve data users. This role leads that work across a defined business domain, directly managing a team … product level, with experience aligning analytics investment to domain prioritiesNice to HaveExperience in a marketplace, e-commerce, grocery or retail analytics contextFamiliarity with semantic and metrics layer tooling, or Python for data automation and pipeline workExposure to AI for Data, including agentic AI methods, semantic layers ...

role will play a critical part in moving Cluttons towards a fully integrated data environment, combining multiple data sources into a consistent reporting layer and delivering actionable insight to leadership. This is a hands-on leadership role, combining strategic design, technical delivery and stakeholder engagement. You will be positioned … lifecycle management. Lead the implementation and use of Microsoft Fabric as the core data platform. Define and manage data ingestion, transformation, modelling and semantic layers. Ensure compliance with information security and regulatory requirements. Reporting & Insight Deliver a standardised reporting suite covering pipeline, timesheets and financial performance across all business ...

hands-on senior role for a strong Python engineer with solid data engineering experience and practical exposure to AI agents. You will build catalogue, semantic, entitlement, and analytical layers that enable agents to work with enterprise data safely and effectively. Requirements: 6+ years building production software in Python, with … time-series stores). Experience in on-premise/regulated environments and their constraints (data residency, auditability, “golden copy never moves”). Familiarity with semantic layers/knowledge graphs and entity resolution. Exposure to policy-as-code (e.g. OPA) or data-access platforms. Awareness of how AI agents ...

intelligence platforms.Develop trusted, fact-based insight experiences that minimise AI hallucinations and provide clear, explainable outputs.Partner with data, BI, and technology teams to optimise semantic models for AI readiness.Apply data science, machine learning, NLP, and advanced analytics techniques to enhance insight generation and anomaly detection.Contribute to the organisation … Applied Analytics, or a related field.Proven ability to develop strategy and influence senior stakeholders, including executive-level audiences.Hands-on experience with enterprise data modelling, semantic layers, and business intelligence platforms (Power BI experience highly desirable).Experience working with LLMs, conversational AI, natural language analytics, or generative AI solutions.Deep understanding ...

Develop trusted, fact-based insight experiences that minimise AI hallucinations and provide clear, explainable outputs. Partner with data, BI, and technology teams to optimise semantic models for AI readiness. Apply data science, machine learning, NLP, and advanced analytics techniques to enhance insight generation and anomaly detection. Contribute … related field. Proven ability to develop strategy and influence senior stakeholders, including executive-level audiences. Hands-on experience with enterprise data modelling, semantic layers, and business intelligence platforms (Power BI experience highly desirable).Experience working with LLMs, conversational AI, natural language analytics, or generative AI solutions. Deep understanding ...

both current reporting and future analytical use cases. Key responsibilities include: Designing and governing enterprise-wide data models across Medallion Architecture layers. Creating curated semantic and analytical data models using dimensional modelling and Kimball methodologies. Defining data modelling standards, governance frameworks, and data feed specifications. Collaborating with Data Engineers … Modelling within large-scale enterprise environments. Dimensional modelling, star schemas, facts and dimensions, and Kimball methodologies. Designing and implementing Medallion Architecture frameworks. Building curated semantic layers within modern cloud data platforms. End-to-end data modelling from source systems through to analytics and reporting layers. Defining and implementing data ...

analytics engineering, dashboards, pipelines, governance, and performance optimization. Create documentation, samples, walkthroughs, and adoption assets for workflows across SQL, ELT/ETL, dbt, orchestration, semantic modeling, BI, and analytics application development. Partner closely with product, engineering, and field teams to identify high-value use cases, develop technical assets … data transformation, orchestration, APIs, SDKs, notebooks, BI tools, and cloud data platforms. Strong understanding of SQL-centric developer workflows, including data modeling, query optimization, semantic layers, transformation frameworks, governance, observability, and dashboard or analytics consumption patterns. Experience building demos, prototypes, reference apps, or production-oriented examples for analytics ...

architecture strategy across a modern Azure Data Lakehouse environment Design and govern enterprise-wide data models across Medallion Architecture layers Create scalable curated and semantic data models using dimensional modelling and Kimball methodologies Define data standards, governance frameworks and modelling best practices across the platform Work closely with Data … Data Architecture experience within enterprise-scale environments Extensive experience with dimensional modelling, star schemas, facts, dimensions and Kimball methodologies Experience designing curated and semantic layers within modern cloud data platforms Strong understanding of Medallion Architecture and Azure-based Data Lakehouse environments Experience establishing governance, standards and data architecture best ...

modeling, analytics engineering, dashboards, pipelines, governance, and performance optimization.Create documentation, samples, walkthroughs, and adoption assets for workflows across SQL, ELT/ETL, dbt, orchestration, semantic modeling, BI, and analytics application development.Partner closely with product, engineering, and field teams to identify high-value use cases, develop technical assets, and continuously … engineering, data transformation, orchestration, APIs, SDKs, notebooks, BI tools, and cloud data platforms.Strong understanding of SQL-centric developer workflows, including data modeling, query optimization, semantic layers, transformation frameworks, governance, observability, and dashboard or analytics consumption patterns.Experience building demos, prototypes, reference apps, or production-oriented examples for analytics, BI, data ...

analytics engineering, dashboards, pipelines, governance, and performance optimization. Create documentation, samples, walkthroughs, and adoption assets for workflows across SQL, ELT/ETL, dbt, orchestration, semantic modeling, BI, and analytics application development. Partner closely with product, engineering, and field teams to identify high-value use cases, develop technical assets … data transformation, orchestration, APIs, SDKs, notebooks, BI tools, and cloud data platforms. Strong understanding of SQL-centric developer workflows, including data modeling, query optimization, semantic layers, transformation frameworks, governance, observability, and dashboard or analytics consumption patterns. Experience building demos, prototypes, reference apps, or production-oriented examples for analytics ...

Align product strategy with business value, regulatory needs, and enterprise capabilities.Enterprise Data Product Ownership: Own and evolve end-to-end data products, including datasets, semantic layers, APIs, and AI-enabled capabilities; Ensure products are scalable, reusable, governed, and aligned to enterprise standards; Drive transition from reporting and pipelines … drive product-led transformation.Preferred Qualifications Experience in sustainability, supply chain, or regulated industries.Familiarity with Qlik, Power BI, or similar tools.Experience working with APIs, semantic layers, and modern data architectures.Exposure to Danaher Business System (DBS) or similar continuous improvement frameworks.Join our winning team today. Together, we’ll accelerate the real ...

Technical Stack & Requirements: AI/ML Stack: Amazon SageMaker, AWS Bedrock. Design Focus: Vector databases, knowledge graphs, and semantic layers. Databricks: Experience with Databricks and Databricks Genie is highly desirable. Core Mandate: Define the standards for "AI-ready" data curation and direct the integration of AI methodologies into existing … Experience and Financials business logic. Qualifications: 6-8+ years of experience. Strong background in AI/ML design and implementation. Ability to architect semantic layers and knowledge graphs. Experience with GitHub Actions for managing codebases. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence ...

future of AI-enabled analytics. Key Responsibilities Design and scale enterprise BI capabilities using Looker and Looker Gemini (GenBI) Develop and optimise LookML models, semantic layers and dashboards Build scalable, reusable BI solutions that enable self-service analytics Work with large, complex datasets to deliver meaningful business insights Drive … solutions within enterprise environments Experience working with cloud data platforms Excellent stakeholder management and communication skills Nice to have: Financial Services experience Experience designing semantic layers and enterprise BI models Passion for AI, GenBI and the future of analytics Deadline for applications is Thursday 6th August at 10:00am. ...

lifeDrive analytics-wide innovation, identifying practical opportunities created by AI, modern analytics tooling and evolving platform capabilities. Help define and execute our strategy for semantic layers, self-service analytics and metric governance. Raise technical standards across the analytics community, improving quality, consistency and scalability. Partner with Product, Data, Engineering … data modelling and analytics architecture. You're able to move comfortably between strategic discussions and technical implementation details. You have a strong understanding of semantic layers (e.g DBT metricflow or LookML), metric governance, self-service analytics and modern BI concepts, with a clear point of view on what good ...

empower self-service data literacy for PMs, design researchers and engineers.Design LLM-ready data foundations for onboarding analytics, including clean business entities, event schemas, semantic definitions, metadata, retrieval-friendly documentation, and evaluation datasets that make data usable by AI systems without losing governance or context.Partnering with your product manager … decomposition, experimentation, causal inference, or product opportunity sizing.Data product ownership: Experience building and owning production-grade analytical assets, such as dbt models, Airflow jobs, semantic layers, metric stores, governed dashboards, or trusted self-serve datasets.LLM-ready data thinking: You understand what makes data usable by AI systems: clean entities ...

client-facing insight depends on engineers being able to find, understand, trust, and use financial datasets at scale. DataHub is Bloomberg’s experience layer for data. What GitHub is for code, DataHub is for data: the place where engineers discover datasets, understand schemas, request access, publish streams, subscribe … only a frontend role, and it is not only a backend infrastructure role. The experience is the full journey: the UI, the APIs, the semantic model, the provisioning flow, the feedback loops, the error states, the defaults, the automation, and the reliability of the systems underneath. The next frontier ...

while integrating people, AI agents and business processes across customer, employee and operational experiences.Shape enterprise AI and data foundations, including AI-ready data platforms, semantic layers, data products and trusted knowledge assets, alongside architectures that enable AI agents to securely interact with enterprise systems and processes.Establish responsible … major enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft.Experience shaping enterprise AI architectures and AI-ready data foundations, including cloud data platforms, semantic layers, data products, AI evaluation, security, governance and responsible AI.Significant consulting or senior client-facing experience, with the credibility to advise executive ...

integrating people, AI agents and business processes across customer, employee and operational experiences. Shape enterprise AI and data foundations, including AI-ready data platforms, semantic layers, data products and trusted knowledge assets, alongside architectures that enable AI agents to securely interact with enterprise systems and processes. Establish responsible … enterprise AI ecosystems such as OpenAI, Google, Anthropic and Microsoft. Experience shaping enterprise AI architectures and AI-ready data foundations, including cloud data platforms, semantic layers, data products, AI evaluation, security, governance and responsible AI. Significant consulting or senior client-facing experience, with the credibility to advise executive ...

will lead the development of trusted data foundations that make AI delivery faster, safer and easier to scale.Designing 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 analyticsShaping agentic architectures and engineering capabilities … processes and human decision-makers, while guiding 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:Significant experience in consulting or senior client-facing roles, acting ...

role requires 6-8+ years in AI/ML design, strong Python skills, and experience deploying AI on AWS. You will drive semantic layers, vector databases, and knowledge graphs while aligning with business logic and #J-18808-Ljbffr ...