24 of 24 Remote/Hybrid Permanent Semantic Layer Jobs

Engineers, Data Scientists, and Data Engineers.You will own our Looker environment end to end — connecting new data sources, modelling a clean and reliable LookML semantic layer, and building the dashboards and self-serve tools that our UA analysts and marketing leadership rely on every day. Beyond building … make a significant impact within the company.Key ResponsibilitiesOwn our Looker environment end to end — connect new data sources, author and maintain the LookML semantic layer (views, explores, models and derived tables), and build the final dashboards, all independently.Design and build self-serve tools and dashboards that empower ...

cohort LTV, and quantify marketing's contribution to pipeline and bookings, in partnership with our GTM/RevOps analytics.Own marketing data models and the semantic layer. Author dbt models on BigQuery integrating HubSpot, Salesforce, Google Analytics and Amplitude, and own the Omni semantic layer so the team … optimisation and reusable datasets.dbt & a cloud data warehouse (BigQuery, Snowflake or similar) — commercial experience building production models, tests and docs.Modern BI with an integrated semantic layer — building self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Deep knowledge of the marketing stack — HubSpot (or similar automation ...

9fin.Explain what's moving the numbers. Diagnose spike drivers and build reproducible analysis frameworks rather than one-off dashboards.Own content datasets and the semantic layer. Author dbt models on BigQuery and own the Omni semantic layer so the newsroom gets fast, trustworthy, self-serve answers.Be the embedded … optimisation and reusable datasets.dbt & a cloud data warehouse (BigQuery, Snowflake or similar) — commercial experience building production models, tests and docs.Modern BI with an integrated semantic layer — building self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Engagement and event analytics — designing tracking/instrumentation and analysing ...

production SLA.This is a platform and product leadership role, not an analytics or BI modelling role. Our Analytics team already owns dbt, the semantic layer, and internal BI — you partner with them and consume their definitions; you don't rebuild what they own.What you'll ownIngestion — event-driven … workPeer to the Head of Analytics — you own platform and external data products; they own meaning and internal BI. You consume their semantic layer as a contract, and neither team duplicates the other.Partner with Product Engineering (our Core and Market Vertical domain teams) as your data producers — defining ...

innovations, enabling Pandora's journey to become the world's leading jewelry company. What to expect from the roleLeading enterprise information architecture design, creating semantic, conceptual, logical models that engineering teams translate into Azure Synapse and Databricks based physical implementations.Architecting domain data models for commerce (store, consumer, marketing, omnichannel … commerce), manufacturing (production, quality, materials), and supply chain (wholesale, inventory, distribution, planning) that reflect business capabilities.Designing data product interfaces and semantic contracts that define how business entities flow through bronze-to-gold transformations, enabling interoperability between domain-owned data products.Developing semantic layer architectures that provide business-oriented ...

future of travel with us About the RoleWe’re looking for an Analytical Engineer to help shape the trusted data models, metrics and semantic layers that power decision-making across On the Beach.This role sits at the intersection of data engineering, business intelligence and emerging AI capabilities. … Engineering, Analytics, Product, Commercial and Technology teams to create high-quality analytical data products.You’ll help define and maintain the business logic, metrics and semantic structures that sit between our data platform and the teams using data every day.You’ll be responsible for:Designing, building and maintaining trusted analytical ...

portfolio companies.Experience with CDC/replication tools feeding a warehouse from an operational database (MySQL, Postgres)Experience with Looker/LookML or another BI semantic layer.Experience in e-commerce, ticketing, or a marketplace business with high-cardinality partner/catalogue data.Experience building or supporting AI/LLM-facing data ...

data models. Author and maintain dbt models, tests and docs that turn raw event streams into reliable, reusable product datasets, and own the Omni semantic layer (topics, metrics, dimensions) so stakeholders trust the numbers.Own instrumentation as a governed product. Design and maintain the event taxonomy, embed a tracking … product analytics tooling. Deep proficiency with Amplitude (or Mixpanel), including designing event taxonomies and conducting behavioural, retention and funnel analysis.Modern BI with an integrated semantic layer. Hands-on experience building intuitive, self-serve dashboards and owning metric definitions (e.g. Omni, Looker, Thoughtspot).Metric design & governance. Owns single-source ...

consistent understanding and reuse - Ensuring data models are optimised for Power BI consumption, including considerations for performance, aggregation, and usability - Supporting the design of semantic layers and ensure alignment between data models and reporting models - Working closely with Business Analysts and Power BI Developers to ensure data structures meet ...

trusted partner to senior leaders, influencing at executive level.Experience defining and embedding end‐to‐end BI delivery methodologies.Strong understanding of data governance, semantic models and trusted data principles.Hands‐on experience delivering BI in an agile, iterative environment.Experience working within insurance or wider financial services data landscapes.Desirable SkillsPractical experience with … rationalising large BI and reporting estates.Exposure to AI‐augmented analytics or automated insight generation.Experience leading BI teams through organisational change or consolidation.Familiarity with enterprise semantic layer technologies.Responsible Artificial Intelligence usage.What We Will Offer YouRecognised and rewarded for a job well done, we have a range of flexible benefits ...

generate actionable insights that drive company growth and inform decision-making.Sr. Data Analytics Developer - Responsibilities:• Design, develop, and maintain enterprise-scale Power BI semantic models (tabular)• Architect scalable and high-performance data models for multi-tenant SaaS analytics• Define best practices for dataset design, governance, and lifecycle management• Optimize … growth and usage scaling• Evaluate and enhance current analytics platform architecture• Partner with teammates for ETL and data pipeline improvements• Provide technical guidance on semantic layer design and analytics best practices• Support cross-functional stakeholders with scalable reporting architecture• Assist in resolving high-priority analytics platform issuesSr. Data ...

company's enterprise data warehouse. Responsibilities include: Dimensional modelling Star schema design Fact and dimension modelling Slowly changing dimensions Master data management Metadata management Semantic layer design Data lineage Business definitions Data quality controls You will ensure the warehouse becomes the trusted source for all business reporting. Data ...

scalable data products (dashboards, models, internal tools) that enable stakeholders to self-serve insightsHelp teams interact more directly with data (e.g. through better abstractions, semantic layers, or AI-powered interfaces)Raise the bar for how AI is used within RAD- sharing patterns, workflows and best practicesCraft clear, compelling data ...

team track and optimize cloud spend through structured monitoring and alerting.BI ResponsibilitiesDevelop, maintain, and improve LookML models, views, and explores across the Looker semantic layerWrite and manage Liquid (Jinja2, Shopify flavor) templating logic for dynamic and parameterized content within LookerWrite advanced SQL queries in BigQuery to support data modeling … debugging, and performance optimizationCollaborate with data engineers on dbt models, ensuring the semantic layer accurately reflects the underlying dataIdentify and resolve data quality and consistency issues across models and exploresReview and refactor existing LookML for performance, maintainability, and accuracyDocument data models and business logic to support long-term ...

Claims value chain.Lead the development and expansion of scalable data pipelines supporting both structured and unstructured claims data.Scale and enhance a Claims ontology and semantic layer that connects structured and unstructured data into a unified business knowledge model, improving discoverability, interoperability, and AI readiness.Collaborate with regional Claims leaders … production.Hands-on experience with Databricks, Snowflake, Azure Data Platform, Azure AI Search, Azure Data Lake Storage, and modern cloud architectures.Experience developing enterprise ontologies, semantic layers, or knowledge graph solutions.Experience building Retrieval-Augmented Generation (RAG), AI Search, or document intelligence solutions.Experience scaling enterprise data capabilities across multiple regions and global ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

operations by embedding insight into workflows, processes, and day-to-day decision-making rather than limiting it to dashboards and reports.Define the knowledge layer, including core business entities, relationships, taxonomies, ontologies, semantic standards, and entity resolution across key business concepts.Establish governance, trust, evaluation standards, and operating models that … operations, translating data insight into operational practice and vice versa.Strong understanding of how AI systems use data, including retrieval-augmented generation, vector search, metadata, semantic layers, knowledge graphs, and agentic workflows.Experience working with complex enterprise data environments, including fragmented systems, inconsistent data quality, and mixed structured and unstructured sources.Demonstrated ...

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 ...

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 analytics Shaping agentic architectures and engineering … 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 ...