151 to 175 of 177 Permanent Semantic Layer Jobs

transformation on large-scale Government projects: Data Engineer with strong hands-on expertise in Palantir Foundry to design + build scalable data pipelines, semantic models + data products. Working closely with data scientists, data analysts, product teams + stakeholders to deliver robust, production grade data foundations that support analytics … Workshop, Quiver). Implementing batch, incremental + streaming ETL/ELT workflows with reusable, production ready components. Data modelling, schema design, build data products, semantic layers, metadata management + governance. Designing + maintaining Foundry ontologies, including object types, link types, property types, and semantic relationships. Supporting Foundry Workshop ...

Architect and modernize enterprise data platforms using Microsoft Fabric, Azure, SQL, Lakehouse and data warehouse technologies Design dimensional data models, star/snowflake schemas, semantic layers and governed enterprise datasets Define scalable data ingestion, transformation, integration and orchestration patterns Architect Azure AI Foundry solutions and enterprise AI applications Design … level experience in enterprise data architecture and engineering Strong hands-on Microsoft Fabric and Azure architecture expertise Advanced SQL, dimensional modeling, data warehousing and semantic modeling skills Experience with Azure AI Foundry or related Azure AI services Practical knowledge of RAG, vector search, grounding and AI agents Strong Python ...

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. … 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 What ...

will help evolve SiriusPoint's BI practice from traditional reporting to AI-driven decision intelligence, helping design, build, and govern enterprise analytical datasets, semantic models, and business ontologies that enable scalable self-service analytics and support AI use cases. Leveraging Microsoft Fabric, Power BI, and emerging AI capabilities … Analytical Data Products: Design and develop curated analytical datasets and data products that support enterprise reporting, self-service analytics, and AI consumption. Construct scalable semantic gold-layer datasets from enterprise data platforms. Define business-friendly data structures that abstract technical complexity from business users. Help evolve the practice ...

systems, including LLMs, agentic AI and cloud-native technologies to solve real-world business challenges at scale. You'll design, build and ship interfaces, semantic layers and controls that let AI agents operate safely inside IFS software, with strong emphasis on security, #J-18808-Ljbffr ...

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 ...

Agentic BI architectures using Snowflake Cortex, Snowpark, AWS Bedrock, SageMaker and LLM technologies Develop architecture patterns for Retrieval Augmented Generation (RAG), vector search, semantic layers, knowledge graphs and enterprise AI assistants Establish governance, security, data quality and Responsible AI standards across data and AI solutions while providing technical leadership … intelligent automation and AI-powered analytics solutions Experience implementing AI technologies such as Snowflake Cortex AI, Snowpark, AWS Bedrock, SageMaker, vector search and semantic search architectures Experience delivering Business Intelligence platforms, self-service analytics solutions and working knowledge of DataOps, MLOps and LLMOps practices Demonstrable experience working in telecommunications ...

Ready Data – Partner with dashboard product owners to shape their dashboards into an AI-ready form the agent can query cleanly and reliably. Semantic Layers & Ontologies – Contribute to semantic models (metrics, definitions, and metadata) so a given metric means the same thing everywhere it's asked about, however … make pragmatic trade-offs to deliver value with minimal supervision. What Would Make You Stand Out: Understanding of data modelling concepts, metadata management, or semantic layers. Exposure to conversational AI, LLM-powered tools, or agent-based workflows. Experience with MCP connections. Familiarity with BI platforms (e.g., Qlik, Power ...

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 ...

designing rigorous experiments, evaluating emerging approaches, and producing evidence-based recommendations that support enterprise adoption. Key responsibilities include: Designing and conducting research into retrieval, semantic and agentic approaches for analytical reasoning and decision support. Building benchmarks, evaluation frameworks and experimental methodologies to assess AI solutions objectively. Prototyping and evaluating … ability to interpret and apply research findings. Python development and AI prototyping skills. And any experience of this would be really useful Knowledge of semantic layers and metrics modelling. Experience of ontologies, knowledge representation, taxonomy development and metadata design. Exposure to knowledge graphs, graph-based reasoning concepts, NL2SQL, Text ...

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 ...

strategies, investment cases, roadmaps and measurable business outcomes. Lead teams of consultants, engineers and architects. Provide technical direction across data platforms, AI, GenAI, semantic architectures and agentic solutions. Ensure AI solutions are secure, governed, reliable and suitable for production. Navigate Financial Services regulatory and risk requirements. Lead proposals, RFPs … business development and selling work. Experience engaging senior stakeholders and presenting at governance/board level. Desirable Experience with Databricks, Azure, AWS, GCP, Snowflake, semantic layers, data products, agentic AI architectures and responsible AI in production would be highly beneficial. This is an opportunity for a senior Data ...

analytics engineering, dashboards, pipelines, governance, and performance optimization. Create documentation, samples, walkthroughs, and adoption assets for workflows across SQL, ELT/ETL, dbt, orchestration, semantic modeling, BI, and analytics application development. Partner closely with product, engineering, and field teams to identify high-value use cases, develop technical assets … data transformation, orchestration, APIs, SDKs, notebooks, BI tools, and cloud data platforms. Strong understanding of SQL-centric developer workflows, including data modeling, query optimization, semantic layers, transformation frameworks, governance, observability, and dashboard or analytics consumption patterns. Experience building demos, prototypes, reference apps, or production-oriented examples for analytics ...

ensure AI use cases are built on the right data foundations. Understand data readiness for AI, including structured data, unstructured data, document ingestion, semantic layers, vector search, permissions and governance. Business Development Support Managing Directors in business development and origination activity across the UK and Europe. Contribute to qualified … Snowflake Cortex, Databricks, Anthropic Claude, OpenAI and related enterprise tooling. Understanding of the data foundations required for AI, including structured data, unstructured data, semantic layers, vector search, permissions and governance. Knowledge of safe and scalable AI delivery, including identity, access, environments, observability, evaluation, auditability and responsible AI controls. Experience ...

Internet of Things. Reply’s services include Consulting, System Integration, and Digital Services. Role Overview: This role focuses on designing and building semantic layers that give organisations a single, shared and machine-readable understanding of their business. You will work across diverse industries, translating complex domains into ontologies … AI. Responsibilities: Facilitate discovery workshops with business and technical stakeholders to understand and model key domains. Design, build, and maintain scalable ontologies, taxonomies, and semantic models that reflect complex business concepts. Develop and operate knowledge graphs end-to-end, including data ingestion, mapping, and entity resolution pipelines. Connect ...

Programme as we replace our BW/BPC landscape with SAP Datasphere and Business Data Cloud (BDC) with SAC as the reporting and planning layer, as part of our S/4HANA transformation. This role is offered as a two-year fixed term contract, running from greenfield platform design … everything is built from scratch, making early design decisions critical. You must be proficient with SAP Datasphere; space design, data flows, replication flows, and semantic modelling. Youll also be charged with developing the standards, documentation, and approach to gathering data requirements. Whilst a big part of the role ...

best-in-class. As the Data Governance & Data Product Lead in the Office of Regulation and Document Governance (ORDG), you will own the foundation layer of ORDG’s Data, Analytics & AI capability — turning policy content into governed, machine-readable data products that AI services, controls and reporting all consume. … control-related data domain — including obligations, controls, standards or procedure content — and its transformation into a governed data product. Working knowledge of Data Mesh, semantic layers, canonical modelling approaches and modern data-catalog/lineage tooling. Familiarity with JPMorganChase data standards, CDAO frameworks and firmwide governance operating models. Experience ...

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 ...

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 ...

Core Data with the CIB Data AI-Readiness framework Define and implement an executable roadmap for agent-ready Core Data, spanning discoverability, entitlements, and semantic context Partner with Technology to make Core Data assets discoverable and consumable by both people and machines Ensure core data assets are registered … described in the Compass catalogue and integrated into Fusion Shape the exposure of reference data through distribution APIs to meet CIB consumption patterns Establish semantic layers to provide business meaning, definitions, and relationships for AI and agentic consumers Identify and eliminate complexity, duplication, and manual handling in Core Data ...

operate across the front, middle and back office. Key Responsibilities Design and build advanced AI solutions, including agentic AI, RAG, GraphRAG, knowledge graphs and semantic layers. Explore emerging technologies and rapidly test where they could create business value. Build prototypes and experiments with production scalability, maintainability and integration … software development. Experience building with LLMs, agents, RAG and modern AI frameworks. Strong understanding of knowledge graphs, large-scale graph technologies, GraphQL and semantic modelling. Experience taking experimental technologies beyond prototypes towards scalable production solutions. Good understanding of APIs, cloud platforms and enterprise integration. Some understanding of data engineering ...

client-facing insight depends on engineers being able to find, understand, trust, and use financial datasets at scale. DataHub is Bloomberg’s experience layer for data. What GitHub is for code, DataHub is for data: the place where engineers discover datasets, understand schemas, request access, publish streams, subscribe … only a frontend role, and it is not only a backend infrastructure role. The experience is the full journey: the UI, the APIs, the semantic model, the provisioning flow, the feedback loops, the error states, the defaults, the automation, and the reliability of the systems underneath. The next frontier ...

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 ...

chemical markets get intelligence, and this role owns the platform foundations that make it possible. You will define the AI-ready data strategy, semantics layer, and MCP-first distribution approach that powers internal product teams, partner integrations, and AI-native customer experiences. This is a highly influential individual contributor … stakeholders to accelerate adoption, integrations, and commercial opportunities Requirements A track record shipping platform capabilities that others build upon, such as APIs, data products, semantic layers, evaluation frameworks, or comparable platform primitives Experience owning platform strategy, roadmap, and delivery outcomes in data, AI, developer platform, or similarly technical product ...