76 to 100 of 116 Permanent Semantic Layer Jobs

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 ...

theory level with no hands-on knowledge.What you will need: Hands-on experience delivering/supporting AI initiatives through Data Management.Core understanding of Ontologies, Semantic Layers, Knowledge Graphs and Context Layers; their differences, use cases and applicability to an organization.Core understanding of Data Agents/Agentic Data Management ...

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. ...

seeking a Senior BI Developer/Analyst to own data domains end-to-end, from raw data to stakeholder-ready insights. You will design semantic layers and deliver self-serve reporting across delivery, quality, investment, and AI adoption metrics. You will collaborate with engineering leadership, shape metrics, and mentor ...

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 ...

Office and other Divisional Data OfficersCollaborate with SME teams building and scaling data platforms (data lakes, warehouses) across on-prem, cloud, and hybrid environments.Implement semantic layers for consistent, governed data views, enabling self-service analytics and explainable AIOversee data quality processes and enforce standards to minimize data duplication … Experience in building & scaling data lakes, data warehouses, and associated data systems.Databases: SQL, PostgreSQL; MongoDB and cloud-based platforms (e.g. Snowflake, Databricks, Redshift).Semantic Layer: Design and implementation for governed reusable data views.Data Governance Tools: Collibra, Alation, Talend or equivalent.Expertise in ETL tools and processes (e.g., Apache NiFi, Talend ...

gold layers within a Medallion Architecture. Create scalable curated data models using dimensional modelling, star schemas, facts and dimensions, and Kimball methodologies. Define semantic data layers, modelling standards, and governance frameworks to improve consistency, quality, and reusability. Manage logical and physical data models, including metadata, business glossaries, data flows … SKILLS AND EXPERIENCE: Strong hands-on experience in Data Architecture and Data Modelling within enterprise-scale environments. Excellent knowledge of dimensional modelling, star schemas, semantic layers, and Kimball methodologies. Experience designing and implementing curated data models within cloud-based data platforms. Strong understanding of logical, physical, transactional, analytical ...

translation of business requirements into rigorous data structures in collaboration with engineering and domain teams Guide teams on the design and effective use of semantic data models, including their application to agentic AI solutions Semantic & Knowledge Modelling Integrate semantic layers with business glossaries, data catalogues, and lineage … tooling Design and maintain semantic models to support agentic-AI capabilities Help develop ontologies, taxonomies, and controlled vocabularies underpinning enterprise metadata and search Define semantic modelling standards and patterns to ensure consistent meaning, interoperability, and AI readiness across data products Guide and control the creation of data domains ...

long-term operating model for Consumer Data Science as the organisation continues its transformation. The wider business is investing heavily across customer platforms, semantic layers, data infrastructure and enterprise transformation programmes, requiring an individual who is equally comfortable discussing modelling approaches, technology architecture and commercial outcomes. Perhaps most compellingly ...

positively impact the education sector.This role sits within the Data & Insights department.Key ResponsibilitiesAct as a subject matter expert for Looker, advocating best practices in semantic modelling, governance, and self-service analyticsDesign, develop, and maintain LookML models, including views, explores, and dashboardsBuild scalable and reusable semantic layers to ensure … processesWhat will you need to succeed Strong experience with Looker and LookML developmentAdvanced SQL skills with several years of hands-on experienceExperience building scalable semantic layers in a BI tool (Looker preferred)Solid understanding of data modelling principles (e.g., star schema, dimensional modelling)Experience with ETL/ELT tools ...

gold layers within a Medallion Architecture. Create scalable curated data models using dimensional modelling, star schemas, facts and dimensions, and Kimball methodologies. Define semantic data layers, modelling standards, and governance frameworks to improve consistency, quality, and reusability. Manage logical and physical data models, including metadata, business glossaries, data flows … SKILLS AND EXPERIENCE: Strong hands-on experience in Data Architecture and Data Modelling within enterprise-scale environments. Excellent knowledge of dimensional modelling, star schemas, semantic layers, and Kimball methodologies. Experience designing and implementing curated data models within cloud-based data platforms. Strong understanding of logical, physical, transactional, analytical ...

enterprise consistency and engineering excellence.Key Responsibilities:1. Enterprise Data Modelling• Lead the enterprise approach to analytical data modelling, including domain models, dimensional models and semantic layers.• Establish reusable modelling patterns and common business entities that create consistency across Data Products.• Reduce duplication and improve the performance, scalability and maintainability … Head of Analytics Engineering to shape the technical roadmap and future engineering capability.Key Technology Areas:Snowflake • DBT • SQL • Python • Git/CI/CD • Semantic Layers • Data Contracts • Data Quality & Observability • Snowflake Cortex • LLMs & AI Agents • AWSSkills & Experience:Must Have• Strong hands-on Analytics Engineering/Data Engineering experience ...

Senior Software Engineer (Backend/Full-Stack, AI-Native) About Us We're rethinking enterprise integration for developers and AI agents with a semantic layer: describe the data you need, and the platform gets it - fast, deterministic, secure, self-repairing, auditable, scalable. Already live with banks and financial ...

Codify the firm’s unwritten methods and judgements into the coworkers and playbooks that run at machine speed. Anchor them through the ontology and semantic layers in Celeste so the agents reason the way its own people do. Earn adoption – Lead the actions that earns Celeste’s adoption, from ...

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.Key Relationships … 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-AB3What ...

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 ...

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 ...

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 ...

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 ...

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 ...