51 to 75 of 88 Remote/Hybrid Semantic Layer Jobs

strategy and influence data governance at scale Involvement in a major cloud migration programme Exposure to emerging areas such as AI-enabled analytics and semantic layer development Clear progression within a structured framework How to Apply If you are an expert in Tableau, apply below ...

detection. A good deal of useful work is not generative.Data and platform foundations. Pipelines and orchestration, lakehouse and streaming patterns, data contracts and quality, semantic layers and lineage. Data foundations often set the limit on what a client can do with AI.Cloud and operations. Hands-on experience with ...

What they're looking for Must-haves 5+ years' experience in data analytics. Advanced SQL skills. Strong BI experience (ideally Looker, Omni, or similar semantic-layer tools). Experience building dashboards and self-serve analytics solutions. Strong stakeholder engagement and communication skills. Ability to independently structure and deliver ...

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. ...

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 ...

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 ...

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 ...

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. ...

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. ...

data platform end-to-end, ensuring accuracy before it reaches the business. You will own the warehouse, the dbt project and semantic layer, and Lightdash dashboards, shaping a single source of truth for KPIs. You’ll report to the Data Lead, collaborate with the CFO, and work ...

similar A startup or scaleup background where you owned something whole rather than a slice of it Nice To Have Text to SQL or semantic layer experience LangGraph, LlamaIndex, LangChain or similar OCR, document parsing and multimodal models Vector databases and retrieval infrastructure at scale Evaluation datasets ...

Product Engineering teams, and drive reliable ingestion, modelling, and orchestration to support data-driven features for customers globally. You will design dbt models and semantic layers, own Dagster orchestration, onboard new data sources at scale, and advance self-serve analytics with agentic workflows and #J-18808-Ljbffr ...

governance, lineage, access, observability, and reliability standards using Databricks and Unity Catalog. Design, build, and continuously improve Databricks Genie spaces, including curated data domains, semantic models, business definitions, trusted metrics, verified queries, permissions, and answer evaluation. Use Databricks AI capabilities to analyze operational data, surface trends and opportunities … PySpark, Delta Lake, cloud data platforms, and enterprise‐scale data pipelines. Hands‐on experience designing and operating Databricks lakehouse architectures, including governed data products, semantic layers, trusted metrics, data quality, and role‐based access. Hands‐on experience building and operating Databricks Genie or closely comparable natural‐language analytics experiences. ...

movement. Implement data-quality checks, controls, lineage, observability, documentation and automated tests to improve trust and supportability. Contribute to AI-ready data products and semantic layers that provide consistent business meaning and governed access to data. Partner with audit teams and data owners to understand requirements, resolve data discrepancies … from DB2, PostgreSQL or comparable enterprise platforms. Exposure to Spark-based processing, orchestration frameworks, CI/CD, containers and cloud data services. Familiarity with semantic layers, metadata management and development of governed, AI‐ready data products. Understanding of data governance, privacy, security, lineage and retention expectations. Experience in financial ...

that improve products for millions of families. You will work with BigQuery, Dataform, Tableau, Amplitude, and Monte Carlo to build robust data models and semantic layers. You’ll partner with Product and Engineering to design experiments, analyse results, and translate findings into actionable product improvements, while mentoring peers ...

framework Creating curated data models using dimensional modelling and Kimball methodologies Defining modelling standards, governance frameworks, and data feed specifications Supporting the design of semantic layers that enable reporting, analytics, and future AI use cases Collaborating closely with Data Engineers and Analytics Engineers in an agile delivery environment Producing … dimensions, and Kimball methodologies Experience designing and implementing Medallion Architecture frameworks Strong knowledge of Azure-based Data Lakehouse environments Experience creating curated and semantic data layers for analytical consumption Proven ability to develop architecture standards, governance frameworks, and modelling best practice Experience working across the full data lifecycle, from ...

partner with Data Engineers, Analytics Engineers, Data Scientists and business teams to turn recurring needs into durable, self-service capabilities. You will own the semantic layer, platform configuration, access governance and production readiness, contributing to a more integrated BI platform across the DoorDash group. #J-18808-Ljbffr ...

identify opportunities others have not yet recognised and influence senior leaders across regions, functions and disciplines. The organisation is investing significantly across customer platforms, semantic layers, data infrastructure and wider enterprise transformation. The successful individual must therefore be comfortable moving between modelling innovation, technology architecture, organisational design and commercial ...

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 ...

domain. Principal Accountabilities Data Product Ownership Own and evolve the Lending data model across BigQuery and Looker Deliver standardised, scalable data models (gold + semantic layers) Ensure data models accurately reflect lending business logic and requirements Drive data quality, validation, and consistency across datasets Technical Leadership Define and implement … transition to GCP and Looker platforms Personal Attributes & Experience Technical Strong SQL and data modelling experience (BigQuery or similar preferred) Experience working with BI semantic layers (Looker preferred) Proven ability to design and deliver scalable data models Domain & Problem Solving Strong understanding of data flows across complex systems (particularly ...

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 ...

continuing acquisition programme. Now we are building the technology that unites them: one AI-first tech stack - the Pulse Platform, with one data layer, and an AI-first client experience for one of the largest advice markets in the country. We're a people-first business where colleagues excel … care. We're obsessed with the client experience, naturally curious, and never stop striving for better. About the role Pivotal Insights is our data layer: a Microsoft Fabric platform bringing data from across the group - CRMs, finance, people and, in time, telephony, marketing and more - into one common data ...

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 ...