126 to 150 of 196 Semantic Layer Jobs in England

dedicated Analytics Engineer in London, hybrid. You’ll blend data engineering, analytics engineering, and business partnership to turn raw data into trusted models and semantic layers for decision-making. You’ll collaborate with Product, Engineering, Risk, Finance, Investment, and Marketing to design pipelines, models, and governance, while shaping ...

impact on how data empowers the organisation. THE ROLE You'll join the data team to lead the design and delivery of a new semantic layer in Looker. You'll work with stakeholders across departments to translate business needs into performant, trusted data models using LookML and dbt. ...

platform maturity. Responsibilities include: Leading end-to-end Tableau development across Tableau Desktop, Tableau Prep, and Tableau Cloud Designing and maintaining scalable data sources, semantic layers, and reporting solutions Defining and embedding Tableau development best practices across the business Building high-quality dashboards that deliver actionable business insights Writing ...

reporting solutions. Responsibilities include: Developing end-to-end Tableau solutions across Tableau Desktop, Tableau Prep, and Tableau Cloud Designing and maintaining scalable data sources, semantic layers, and reporting frameworks Promoting Tableau development best practices and supporting consistent delivery standards Building high-quality dashboards that provide actionable business insight Writing ...

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 ...

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 ...

understanding of how AI capabilities are embedded within existing business systems and workflows.Exposure to data platform architecture (Snowflake, medallion/lakehouse patterns, semantic layers) and how governed enterprise data enables AI at scale.Track record of leading enterprise transformation through influence — driving adoption, managing change, and building cross-functional alignment ...

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 ...

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 ...

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 ...

robust, high-performance real-time data backbone. You will lead data pipelines, integrate Salesforce Marketing Cloud, CDP, and SCV sources, and own the semantic layer with Cube.js for self-serve analytics. You'll collaborate with data architects and stakeholders, mentor junior engineers, and work across ...

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 ...

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 ...

Coaching analysts and BI developers on SQL, DAX, data modelling, visual design and engineering hygiene. Working closely with Data Engineering on changes to the semantic and curated layer and data marts. Delivering complex analytics workstreams end-to-end, and working within an Agile framework to break down requirements … broker or specialty (re)insurer. Advanced SQL, including query optimisation and working with the Azure data stack(Data Factory, Synapse/Fabric, SQL-based semantic layers). Advanced Power BI: data modelling (star schemas), advanced DAX, Power Query/M,performance tuning, RLS and deployment via pipelines. Astrong understanding ...

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 ...

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 ...

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. ...

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. ...

process high‐volume sportsbook events (bets, pricing, settlements). Curated data assets powering trading analytics, risk monitoring, and customer personalisation models. Integration with semantic layers, BI tools, and machine learning platforms. Data governance and metadata tooling to improve transparency, trust, and reuse across the organisation. Your Experience 5+ years … Nice to Have Experience in sports betting, trading, or financial data domains. Familiarity with event‐driven architectures and real‐time data products. Experience with semantic layers (e.g. Cube.js) or metrics‐layer design. Exposure to data governance and metadata tools (e.g. OpenMetadata, Hive Metastore). Experience supporting machine learning ...

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 ...

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 ...

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 ...

architectures and data platforms End-to-end data pipelines (ingestion > transformation > visualization) Hands-on understanding (not necessarily deep execution) of: Power BI (data modeling, semantic layers, KPI standardization) Modern data platforms: Microsoft Fabric (preferred) or Snowflake/equivalent cloud data platforms Data integration patterns, including: APIs ETL/… improvements across all key functions Improve cybersecurity coverage across all sites Rationalize and optimize: MSP landscape Infrastructure footprint Build a high-performing IT leadership layer (Infra + Data/Apps) Compensation Information UK 90-110k #J-18808-Ljbffr ...

Work with stakeholders to gather, analyse and document reporting requirements. Translate business needs into practical and user‐centred reporting solutions. Develop and maintain scalable semantic models and datasets using Power BI best practice. Create and optimise DAX measures, calculations and business metrics. Use Power Query and data transformation techniques … BI. Experience working with Dataverse, Dynamics 365 and Power Platform data sources to develop reporting and analytical solutions. Strong experience creating data models and semantic layers to support reporting and analytics. Advanced knowledge of DAX and experience developing complex calculations and measures. Strong experience using Power Query and data ...