12 of 12 Permanent Semantic Layer Jobs in England

function. The Role As a Senior Analytics Engineer, you will be responsible for transforming raw data into well modelled, business ready data marts and semantic layers. You will take ownership of dimensional modelling, dbt transformations, and core metrics that power BI tools used across the business. This role blends … multi market initiatives. Key Responsibilities * Design and own dimensional data models using Kimball methodology* Build and maintain dbt pipelines from raw to gold layer marts* Define and enforce modelling, testing, and documentation standards* Own elements of the semantic layer and core business metrics* Translate technical schemas into ...

testing, version control and code deployment. Pipeline Orchestration: Architect reliable data workflows to manage complex dependencies and ensure timely data delivery. Data Modelling & Quality Semantic Layer Design: Partner with the Business Systems Team to design optimised data models, ensuring seamless integration with downstream BI tools. Business Logic Standardisation … snapshots for data recovery and handling both batch and streaming data patterns. Transformation & Orchestration Data Build Tool: Strong experience using dbt for the transformation layer (cleaning, testing and documenting data models). Orchestration Tools: Experience designing and scheduling workflows using tools like Airflow, Prefect or platform-native tools. Infrastructure ...

scalable data pipelines using Azure Data Factory and Databricks to automate data ingestion, transformation, and processing workflows. Create and maintain dimensional data models and semantic layers that support business intelligence and analytics use cases. Build and optimise data transformation workflows using dbt, SQL, and Python to create clean, well ...

Building data pipelines in dbt , transforming data from bronze to gold layers using Kimball methodologies Implementing data quality frameworks and testing strategies Owning the semantic layer for BI tools such as Looker and Power BI Supporting self-service analytics and improving data literacy across the business Acting … Analytics Engineer or similar role Advanced SQL and data modelling skills Hands-on experience with dbt and modern analytics stacks Experience supporting BI and semantic layers Comfortable working in cross-functional team If you are interested in the role please apply. To follow please message me on LinkedIn ...

using tools such as SQL, Power BI, Databricks Skills & Experience: Strong SQL, Power BI and financial data modelling Experience working with enterprise data models, semantic layers, or governned data domains Proven experience partnering with senior finance and business stakeholders Strong communications skills with the ability to influence decisions ...

responsibilities: Lead customer onboarding for analytics platforms, delivering training and technical support. Enrich datasets for AI/LLM applications, including metadata management and semantic layers. Monitor Natural Language Query (NLQ) performance and implement optimisation strategies. Develop and maintain a strategic roadmap for platform scalability and accuracy. Design and develop ...

aware that finding a single individual covering every area of expertise is unlikely. However, they idea candidate would have: Strong knowledge of semantic layer design and optimization (e.g., LookML, dbt, or similar frameworks). Hands-on experience integrating and fine-tuning Large Language Models (LLMs) for conversational analytics. ...

some trips to client offices and HQ Lead the design and delivery of complex, AI-native client engagements, spanning agentic systems, retrieval architectures and semantic layers. This is a senior, hands-on consulting role combining deep technical leadership with strong client presence, shaping both client outcomes and the firms ...

London HQ per month Role Overview Lead the design and delivery of AI-native transformation initiatives for insurance clients, spanning agentic systems, retrieval architectures, semantic layers and decision intelligence click apply for full job details ...

some trips to client offices and HQ Lead the design and delivery of complex, AI-native client engagements, spanning agentic systems, retrieval architectures and semantic layers. This is a senior, hands-on consulting role combining deep technical leadership with strong client presence, shaping both client outcomes and the firms … prompt frameworks and evaluation loops Multi-agent architectures, including planning, delegation, safety constraints and monitoring Retrieval and vector-based systems, embeddings, structured reasoning and semantic workflows Ontology and knowledge modelling literacy to enable precise reasoning and data alignment Integrations and automation via APIs, tools and enterprise systems Prompt engineering ...

London HQ per month Role Overview Lead the design and delivery of AI-native transformation initiatives for insurance clients, spanning agentic systems, retrieval architectures, semantic layers and decision intelligence. This is a senior, hands-on consulting role combining deep AI engineering expertise with strong client-facing presence, shaping both … human-in-the-loop controls Retrieval and vector-based systems over policy wordings, endorsements, claims files, loss runs, underwriting guidelines and regulatory documentation Semantic layers, ontologies and knowledge models aligned to insurance data structures, coverage logic and risk taxonomies Integrations with core insurance platforms (claims systems, PAS, underwriting workbenches ...

London HQ per month Role Overview Lead the design and delivery of AI-native transformation initiatives for insurance clients, spanning agentic systems, retrieval architectures, semantic layers and decision intelligence. This is a senior, hands-on consulting role combining deep AI engineering expertise with strong client-facing presence, shaping both … human-in-the-loop controls Retrieval and vector-based systems over policy wordings, endorsements, claims files, loss runs, underwriting guidelines and regulatory documentation Semantic layers, ontologies and knowledge models aligned to insurance data structures, coverage logic and risk taxonomies Integrations with core insurance platforms (claims systems, PAS, underwriting workbenches ...