26 to 50 of 169 Semantic Layer Jobs in England

with. Experimentation rigour. Lead A/B tests, holdouts, sample sizing, and post-test analysis to support confident decisions. Own certified metrics and the semantic layer for your squad’s domain. Ensure metrics are consistent, documented, accessible, and trusted. Applied AI as a working tool. Use LLMs … would also be great if you have: Familiarity with AI evaluation patterns - eval sets, scorecards, guardrails for non-deterministic outputs. Working understanding of the semantic layer and certified metrics. Hands-on experience prototyping data-driven product features Experience as the data expert in an Agile squad alongside Product ...

scale its data ecosystem into a true single source of truth. You will own the Azure‐centric lakehouse foundations and help evolve toward a semantic layer and lakehouse architecture. You will design pipelines, implement metrics‐as‐code for KPIs, and partner with AI/ML engineers to power ...

merchandise group, is looking for an analytics engineer or data analyst to own analytical domains end-to-end. You will define metrics in the semantic layer with stakeholders, model data in dbt, and ensure trusted answers are produced wherever used. You will partner with operations, commercial, finance ...

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 ...

tooling to accelerate delivery Clear, consistent definitions of key business metrics Improved data reliability and fewer reporting discrepancies WHAT YOU'LL OWN The transformation layer (dbt) and semantic layer (Looker) Core business metrics and reporting definitions Data quality and testing frameworks WHAT ...

data platform aligned to the business and product strategy. Own and evolve the data architecture for Quantios Insights, including data ingestion patterns, lakehouse design, semantic modelling, and analytical layers. Define architectural guardrails and reference patterns for Databricks to support customer deployment flexibility. Contribute to the long-term roadmap … domain-driven canonical data models for all Quantios products and cross-product datasets. Architect medallion/lakehouse models (bronze, silver, gold) using Databricks. Ensure semantic models, KPIs, and analytical structures are consistent, scalable, and aligned with business requirements, and serve whichever BI and application layers consume them. Guide Data ...

established, and ready for someone to take to the next level. You’ll be the go‐to expert for our lakehouse/warehouse architecture, semantic models, and the pipelines that keep data flowing reliably across the business. This is a hands‐on senior individual contributor role … repository, including code quality, branching strategy, CI/CD, and release governance. Define and enforce best practices for data modelling, ingestion, transformation, orchestration, and semantic layer design. Drive platform reliability, performance, security, and cost optimisation across lakehouse/warehouse workloads. Act as technical lead for solution design, incident ...

will lead a team of 8-10 people across Data Engineering, Analytics and AI. You will own the data platform, semantic layer, analytics estate and AI enablement agenda, while working closely with business and technology leaders across Hyve. Your immediate priorities will be to complete and embed … standard Hyve semantic data model; rationalise hundreds of duplicated reports into the core tens that matter; enable genuine stakeholder self‐service; and champion meaningful generative and agentic AI use cases across the business. This is a strategic and hands‐on leadership role. You will combine data architecture, engineering, analytics ...

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 ...

techniques; ETL/ELT processes and dimensional modelling. Experience designing data models and documentation that are usable by AI/LLM-based analytics tools (semantic layers, metadata, access controls). In-depth knowledge of cloud data infrastructure, ideally GCP (Azure or AWS also considered). Excellent problem-solving skills ...

Define the approach for integrating data from multiple business systems into a unified, governed warehouse Own the definition of data catalogues and a semantic layer, working with stakeholders across the business Design the approach for a self-serve query layer, including conversational and AI-driven interfaces ...

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 ...

career path that is difficult to develop in a purely technology-focused role. Purpose of the role Responsible for the finance data and ontology layer on which agentic solutions depend. Builds the entities, relationships, definitions, lineage and data contracts sourced from live ERP and EPM systems to a standard … that supports controlled and auditable agent behaviour. The role owns governed finance data products, semantic models and retrieval-ready data services that are secure, permission-aware, observable and suitable for AI, analytics and decision intelligence. Responsibilities Build and extend the finance ontology covering supplier, invoice, customer, receivable, journal, account ...

still tells you what's changed, why it matters and what to do about it. Under it we're building the semantic layer, so every answer uses the same definitions, the signal layer that spots what's changed for a client, and the reasoning layer … That means making your case to engineers, product and the commercial team, and bringing them along with you. What You'll Work On The semantic layer. Measures, dimensions and definitions the model is allowed to use, so every answer it gives is the same answer. Yours to grow, persona ...

still tells you what's changed, why it matters and what to do about it. Under it we're building the semantic layer, so every answer uses the same definitions, the signal layer that spots what's changed for a client, and the reasoning layer … That means making your case to engineers, product and the commercial team, and bringing them along with you. What You'll Work On The semantic layer. Measures, dimensions and definitions the model is allowed to use, so every answer it gives is the same answer. Yours to grow, persona ...

/CD, Git workflows, and Infrastructure as Code (Terraform). AI-ready architecture (desirable): Experience preparing data infrastructure for GenAI and agentic AI - including semantic layers, retrieval (RAG), vector search, knowledge graphs, or Model Context Protocol. We work together. Your team and the people you will work with... ...

optimize robust ETL/ELT pipelines that handle multi-terabyte data volumes with high reliability and performance. Own and evolve our BI and semantic layer (Looker/LookML), enabling intuitive, performant, and truly self‐service analytics. Partner closely with Data Scientists, Product Managers, and Engineers to streamline analytical ...

data processing architectures that support AI-driven analytics, recommendations, forecasting, and intelligent automation. Optimise cloud data platforms for AI scalability, including data lakehouse architectures, semantic layers, and high-performance data retrieval patterns. Stays current with Snowflake features, best practices, and industry trends in cloud data platforms. Performs additional related ...

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 ...

looking for a Senior Data Analytics Engineer to own the analytics layer and become the main point of contact for data across the business. You’ll work closely with Product, Marketing, Finance and Operations to understand their data requirements, turn them into reliable models and metrics, agree priorities … also support the Data Analyst in working confidently with the data. You’ll be joining an established data platform with the ingestion layer already in place. Your focus will be on the modelling, analytics and reporting layer built on top of it. What You’ll Own Data Modelling ...

loss ratio, so we understand the risk and commercial impact of what we ship, not just conversion Own metric definitions and contribute to our semantic layer, helping ensure the business works from a consistent version of each number Collaborate with BI and Data Engineering colleagues on analytical ...

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. ...

collaborative development and version control. Familiarity with reporting/BI tools like Looker. Preferred Qualifications Python expertise for automation, integration, and orchestration Experience with Semantic layers Experience with orchestration tools like Airflow. Knowledge of modern software engineering practices applied to data (e.g., modularity, code review, testing). Our Vision ...

vision and hands-on execution of our next-generation Object-Centric Data Fabric . You will transition traditional application-centric architectures into a centralised semantic layer that seamlessly unifies multi-stream operational data—including Electronic Data Capture (EDC), patient telemetry, and real-world health datasets. In this role … optimization, and regulatory documentation. This allows you to focus on driving high-impact platform architecture. Data Fabric & Lake Architecture: Architect and evolve the enterprise semantic data fabric, converting multi-stream clinical execution datasets into an object-centric model. Design and execute a modern Data Lake strategy centred on Apache ...

e.g. Consumer Duty, CASS, KYC/AML, GDPR) into concrete data controls, monitoring and reporting. Maintain and evolve the analytics glossary, data catalogue and semantic layer so compliance-related metrics are clearly defined, consistent and auditable. Support internal and external audit requests with well-documented, reproducible analysis. Modern … Dashboards Build and maintain dashboards and reports using modern BI tools. Ensure metrics are correctly defined, documented, and consistent with the data catalogue and semantic layer. As the role broadens, support wider analytics team with ad hoc analysis outside governance and compliance. Data Quality & Documentation Work with the Chief ...