1 to 25 of 34 Semantic Layer Jobs in England

goes to the questions that need real thought.You'll set the standards for how analytics is built here: governed metric definitions and a shared semantic layer so numbers agree across the business, a well-maintained data catalog and ontology so data assets are discoverable and trusted, version control … questions confidently and safely for themselvesPartner with the Data Science and Enterprise AI team to deliver AI-enabled self-service analytics, grounded in governed semantic views, so colleagues can query trusted data directly in natural language rather than waiting on bespoke reportingInsight and deliveryBuild and maintain lightweight data products ...

Great Lakes Data & BI team, responsible for building and maintaining data products within the Azure Databricks lakehouse, including Silver and Gold table transformations and semantic layer outputs, and for diagnosing and resolving data issues arising from the data intake platform. Reporting to the Data & BI Lead, the successful … with medallion architecture, and comfortable contributing technical input into modelling discussions alongside IT Experience with Databricks, including Delta Lake; familiarity with Unity Catalog and semantic layer/consumption-layer tooling is a plus (Power BI & Databricks Dashboards) Power BI experience, able to build and maintain dashboards ...

ownership of our internal reporting tools and partner-facing data products, including OSP Insights. By establishing robust evaluation frameworks and aligning semantic architecture with business outcomes, you will ensure our global partners and internal stakeholders derive maximum value from certified operational data. Key Responsibilities: Define and execute the group … analytics, using Claude and Model Context Protocol (MCP) to enable self-serve access to certified data. Collaborate with Analytics Engineering to shape the unified semantic layer migration onto dbt MetricFlow. Establish evaluation frameworks, telemetry, and logging to rigorously assess AI accuracy, system performance, and metric trust. ...

Tableau access management and application management Experience working with enterprise data discovery, analytics, and BI software tools such as Tableau, PowerBI and others for semantic-layer-based data discovery. Experience in enabling the BI self service capability for the organisation Experience and knowledge of big data platforms ...

optimization. Experience with cloud data platforms (e.g., Snowflake, Azure Synapse, BigQuery, Databricks). Expertise in data modeling concepts: star/snowflake schemas, dimensional modeling,semantic layers, and performance tuning at scale. Experience with Python or R for data wrangling and exploratory analysis. Analytical & Business Acumen Strong ability to decompose ...

following technologies: Data Processing: Apache Spark/PySpark Workflow Orchestration: Apache Airflow Containerisation: Kubernetes Cloud Platform: Microsoft Azure Data APIs & Semantic Layer: CubeJS Programming Languages: Python, SQL Essential Skills & Experience Degree in a STEM discipline, ideally Computer Science, Software Engineering, or a related field. Minimum of 5 years … Experience designing and building scalable, production-grade data pipelines. Desirable Experience Experience working within cloud-native Azure environments. Knowledge of modern analytics platforms and semantic data layers. Previous mentoring or technical leadership experience. Apply If you're a passionate Senior Data Engineer looking to work on complex data challenges ...

data integration, migration or transformation, ideally involving General Ledger and financial reporting Deep understanding of data modelling, including dimensional modelling, normalisation/denormalisation and semantic layers Experience with Microsoft Azure, Fabric, ETL/ELT, data pipelines and Lakehouse/Warehouse architecture Ability to translate architecture into practical implementation plans ...

services experience. Distributed computing environments. Streaming and low-latency data processing. Containerisation and orchestration technologies. Infrastructure-as-Code tooling. Exposure to AI-focused technologies, semantic layers or agentic architectures. ...

strong BI and reporting focus, with a meaningful element of data modelling and collaboration with Analytics Engineering. You will build trusted data pipelines, establish semantic layers with clearly defined metrics and design self-serve reporting. You will enable analysis at scale and help teams monitor performance, identify opportunities ...

transformation programmes. What you'll be doing Supporting solution architecture and technical design Building scalable, production-grade data platform Developing data models, pipelines and semantic layers Working directly with clients to understand requirements and shape delivery roadmaps What we're looking for 24 years' experience in data engineering ...

architecture and roadmap. Design, develop and optimise data pipelines, lakehouse and warehouse solutions to support reliable data delivery. Build and maintain scalable data models, semantic layers and reporting solutions. Work extensively with SQL, Python and the wider Microsoft data ecosystem. Develop and enhance Power BI reporting to provide meaningful … automation. Good understanding of lakehouse and data warehouse architectures. Experience developing and maintaining data pipelines and orchestration processes. Knowledge of Power BI, including semantic models, DAX and reporting. Experience with Git, CI/CD and modern software engineering practices. An understanding of data governance, security, quality and platform performance. ...

real-time data-processing solutions. Lead the design of a Customer Data Platform. Build and evolve a lakehouse architecture using AWS technologies. Create governed semantic models, consistent metrics and clear data definitions. Enable secure, self-service data analysis using modern AI tooling. Automate manual, repetitive or fragile data processes. … open table formats such as Iceberg. Medallion architecture and dimensional data modelling. Strong SQL and Python. SQL Server, SSIS/SSDT and Power BI. Semantic layers, common metrics and data glossaries. Data governance, lineage, retention, classification and auditability. Managing and developing a small technical team. You should also ...

function that sets new standards for efficiency, innovation and business value.Working closely with central data teams and federated BI communities, you'll ensure reporting, semantic data models, analytics and insight solutions are delivered consistently, effectively and in line with organisational objectives, maximising business value from data and analytics investments.You … developers and analysts, promoting high standards of quality, performance, usability and governance. The role drives innovation, consistency and reuse across analytical products, semantic models and KPI frameworks, fostering a scalable, trusted and high-performing analytics ecosystem while championing modern BI, AI-assisted development and data-driven decision-making.We ...

curated, analytics-ready data within our Lakehouse environment. You'll translate complex business requirements into robust SQL and PySpark pipelines, own the data serving layer, and ensure data is well-modelled, governed, performant and ready for consumption across analytics and BI. You'll also provide technical leadership and mentorship … helping to establish best practices across the team. Key Responsibilities: Design and deliver dimensional and semantic data models for analytics. Define and maintain KPIs, conformed dimensions and consistent data definitions. Develop and optimise SQL and PySpark pipelines using Databricks. Ensure high standards of data quality, testing, performance and observability. ...

role in developing high-quality, analytics-ready data across its modern data platform. This is an opportunity to take ownership of the curated data layer within a Databricks Lakehouse environment, translating complex business requirements into robust data models and transformation pipelines that support reporting, analytics, and business decision-making. … Responsibilities: Lead the design and development of curated, analytics-ready dimensional and semantic data models. Build, maintain and optimise complex SQL and PySpark transformation pipelines within Databricks. Define and maintain KPI definitions, conformed dimensions and consistent business logic across data domains. Ensure data quality, integrity, testing, observability and performance ...

value, technical feasibility, data readiness and strategic alignment. Collaborate closely with data engineering, data product and technology teams to ensure data infrastructure, pipelines and semantic layers support advanced analytical needs. Translate complex data and modelling outputs into clear, compelling narratives tailored to executive, senior leadership and operational audiences. Define … processes, data quality, metric definition, analytical engineering principles and collaboration with data engineering teams. Experience designing, governing and scaling analytical products, insight frameworks, semantic layers, dashboards or measurement solutions used across multiple business areas. Advanced hands-on capability in SQL, Python or R for advanced analysis, automation, statistical modelling ...

transformation programmes. What you'll be doing Supporting solution architecture and technical design Building scalable, production-grade data platform Developing data models, pipelines and semantic layers Working directly with clients to understand requirements and shape deli click apply for full job details ...

data strategy, requirements and priorities. You will help define and drive the capabilities, patterns and practices needed to make enterprise data AI-ready, including semantic layers, knowledge graphs, and ontologies to ensure trusted, governed and scalable use of enterprise data by AI applications and agents. The successful candidate will … relevant experience across data and AI, including significant experience leading complex enterprise initiatives. Demonstrated experience designing or delivering AI-ready enterprise data capabilities, including semantic layers, knowledge graphs and ontologies. Strong practical understanding of modern AI technologies and architectures, including generative AI, large language models, retrieval approaches and agentic ...

will further enhance productivity and prioritisation within the wider Marketing Analytics team leveraging these same technologies into effective and streamlined processes such as semantic layers, impact calculations and AI-skill alignment across teams. Rather than just reporting the financials, you'll focus on the why to pinpoint the highest … journey. Strong proficiency in 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. Proven competencies in identifying analytical opportunities within financial/marketing processes and reporting on them effectivelyStrong ability to understand ...

base, 2 trips to office per month Lead the design and delivery of complex, AI-native client engagements, spanning agentic systems, retrieval architectures and semantic layers. This is a senior, hands-on consulting role combining deep technical leadership with strong client presence, shaping both client outcomes and the firm … orchestration patterns, prompt frameworks and evaluation loopsMulti-agent architectures, including planning, delegation, safety constraints and monitoringRetrieval and vector-based systems, embeddings, structured reasoning and semantic workflowsOntology and knowledge modelling literacy to enable precise reasoning and data alignmentIntegrations and automation via APIs, tools and enterprise systemsPrompt engineering at scale, including ...

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 … 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 ...

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 … reinventing Data Management & Governance for the AI era. 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. Data ...

foundations that make AI delivery faster, safer and easier to scale. Leading design and delivery teams to build 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 analytics Designing and embedding engineering capabilities … human decision-makers, while supporting 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: Experience in consulting or client-facing roles, building trusted senior client ...

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 ...

enabled applications, intelligent workflows and data-driven products Advise clients on the development of modern data ecosystems, including cloud platforms, data products and semantic modelling Oversee the design of AI solutions that integrate effectively with existing technology, operational processes and business teams Establish appropriate frameworks for AI governance, risk … enterprise AI architectures and understanding how AI agents interact with enterprise systems, data, business processes and people Good understanding of modern cloud data platforms, semantic layers, data products, AI evaluation, security, governance and responsible AI Strong commercial capability, with experience shaping propositions, developing opportunities and leading client engagements Excellent ...