11 of 11 Semantic Layer Jobs in England

data retrieval and generation. Develop APIs and microservices and dbt to integrate RAG capabilities with existing data sources (mainly user behaviour data, metadata and semantic layer, stored in Redshift, but also other sources e.g. HR systems, legal repositories, SharePoint, etc.). Manage and optimize LibreChat UI and Openweb … UI Pipelines for chatbot interactions. Data Engineering & Integration: Build efficient data pipelines to support LLM-based querying, semantic search, and metadata retrieval. Integrate structured (SQL-based) and unstructured (documents, reports) data sources for real-time and batch processing. Maintain and troubleshoot Airflow pipelines for embedding extraction and document processing. … in SQL, Redshift, and data warehousing concepts. Experience integrating structured and unstructured data sources for AI-driven applications. Knowledge of dbt, metadata management, and semantic search. Familiarity with React or other frontend frameworks for building intuitive UIs. Cloud deployment experience in AWS or Kindred Cloud. Experience with Kubernetes, Terraform More ❯

. You'll coach and mentor Senior Data Engineers, Data engineers & Associate Data Engineers. You'll create high complexity BI solutions including data mart, semantic layer, and reporting & visualisation solutions in recognised BI tools such as PowerBI. Experience & knowledge: Requires extensive experience of designing and building end to More ❯

. You'll coach and mentor Senior Data Engineers, Data engineers & Associate Data Engineers. You'll create high complexity BI solutions including data mart, semantic layer, and reporting & visualisation solutions in recognised BI tools such as PowerBI. Experience & knowledge: Requires extensive experience of designing and building end to More ❯

mentoring a high-performing team of Power BI developers and analysts, promoting quality, consistency, and continuous learning. Creating scalable, high-performing data models and semantic layers using Power BI datasets, working closely with data engineers to optimize integration with Databricks. Driving end-to-end lifecycle management of reporting assets More ❯

plus. Solid understanding of the full SDLC, cloud environments (AWS/Azure/GCP), and Big Data technologies. Familiarity with modern EDM architectures and semantic layer design. Personal Attributes: Strong analytical, problem-solving, and critical thinking abilities. Confident communicator, able to explain technical concepts to non-technical stakeholders. More ❯

plus. Solid understanding of the full SDLC, cloud environments (AWS/Azure/GCP), and Big Data technologies. Familiarity with modern EDM architectures and semantic layer design. Personal Attributes: Strong analytical, problem-solving, and critical thinking abilities. Confident communicator, able to explain technical concepts to non-technical stakeholders. More ❯

staking, restaking, MEV, and validator rewards A proven track record of architecting scalable and efficient data modelling strategies across an organisation Experience in creating semantic layers for consistent and intuitive data access for stakeholders Benefits What we offer: Exposure to cutting-edge cryptocurrency and blockchain technologies Opportunities for internal More ❯

skill in SQL and/or Python coding are required. Training can be provided for DBT and Snowflake. Experience in using or implementing a semantic layer is a plus. Tableau experience is a plus; ability to build dashboards. Why Join Us? Join our team and contribute to a More ❯

ensure maximum value is delivered in each 'sprint.' Skills and Experience Specification: Essential: Extensive knowledge of data warehousing, including physical modeling, ETL, ELT, CDC, semantic layers, and reconciliation principles. Strong SQL knowledge. Proficient in Python, Terraform, Snowflake, and AWS. Experience in monitoring, automated testing, reporting design, and dashboarding. Critical More ❯

For Experience in insurance, payments, fintech, or other regulated industries. Building pipelines for AI/ML models using tools like Mosaic ML. Working with semantic layers and advanced data modelling techniques. Implementing automated testing frameworks like Great Expectations or PyTest . Ready to lead the charge in a company More ❯

For Experience in insurance, payments, fintech, or other regulated industries. Building pipelines for AI/ML models using tools like Mosaic ML. Working with semantic layers and advanced data modelling techniques. Implementing automated testing frameworks like Great Expectations or PyTest . Ready to lead the charge in a company More ❯