51 to 75 of 172 Semantic Layer Jobs

high quality, compliant code You’ll coach and mentor Associate data engineers. You’ll create low to high complexity BI solutions including data mart, semantic layer, and reporting & visualisation solutions in recognised BI tools such as Power BI. Experience & knowledge Requires experience of designing and building ...

resolution, improving client experience and driving operational efficiency Demonstrate control environment improvements and reduction in toil through common tooling and frameworks; uplift the metadata (semantic layer) of existing data to support AI and Natural Language Query (NLQ) usage, accelerate adoption of Mesh data architecture, reduce consumer friction ...

data processing architectures that support AI-driven analytics, recommendations, forecasting, and intelligent automation. Optimise cloud data platforms for AI scalability, including data lakehouse architectures, semantic layers, and high-performance data retrieval patterns. Stays current with Snowflake features, best practices, and industry trends in cloud data platforms. Performs additional related ...

business domains and platforms Visualization, BI & Data Product Delivery Partner with analytics and product teams to deliver high‐quality datasets, dashboards, and visualization‐ready semantic layers Translate business requirements into scalable data models and consumption patterns for operational and executive insights Support adoption of data products by ensuring performance ...

grade machine learning or generative AI solutions. Experience with agentic development patterns, including tool use, workflow orchestration, and evaluation of agent behavior. Experience with semantic layers and ontology design, including defining consistent business concepts, relationships, and metadata for analytics and AI use cases. Relevant AWS AI certifications, such ...

LLMOps, Retrieval-Augmented Generation (RAG), Docker, DevOps, AI/ML libraries, Azure Cloud, REST, QE DevOps, SQL Server, CAG, Tokenizer, Encoder/Decoder, Guardrails-Semantic layer, LLM response layer, UiPath, CSS, HTML, and Microsoft Visual Studio; and 5 years of experience performing ROI driven test automation, automation ...

/CD with Platform (Repos, Git, deployment pipelines, Terraform Jobs/Infrastructure as Code). Analytics Engineering Model curated gold datasets, dimensional models, and semantic layers for BI (Tableau/PowerBI). Optimise SQL Warehouses for performance, concurrency, and cost; maintain versioned metric definitions. Document tables with catalog cards ...

volunteer roles, work experience, etc.)Technical Skill SetData Architecture & Platforms Cloud data platforms, SQL, ingestion pipelines (batch, streaming, CDC), ETL/ELT, data modelling, semantic layers, integration patterns, and the TCO trade-offs of building with hyperscalers vs. Salesforce. Deep familiarity with Informatica (IDMC) for enterprise data integration ...

following technologies: Data Processing: Apache Spark/PySpark Workflow Orchestration: Apache Airflow Containerisation: Kubernetes Cloud Platform: Microsoft Azure Data APIs & Semantic Layer: CubeJS Programming Languages: Python, SQL Essential Skills & Experience Degree in a STEM discipline, ideally Computer Science, Software Engineering, or a related field. Minimum of 5 years … Experience designing and building scalable, production-grade data pipelines. Desirable Experience Experience working within cloud-native Azure environments. Knowledge of modern analytics platforms and semantic data layers. Previous mentoring or technical leadership experience. Apply If you're a passionate Senior Data Engineer looking to work on complex data challenges ...

following technologies: Data Processing: Apache Spark/PySpark Workflow Orchestration: Apache Airflow Containerisation: Kubernetes Cloud Platform: Microsoft Azure Data APIs & Semantic Layer: CubeJS Programming Languages: Python, SQL Essential Skills & Experience Degree in a STEM discipline, ideally Computer Science, Software Engineering, or a related field. Minimum of 5 years … Experience designing and building scalable, production-grade data pipelines. Desirable Experience Experience working within cloud-native Azure environments. Knowledge of modern analytics platforms and semantic data layers. Previous mentoring or technical leadership experience. Apply If you're a passionate Senior Data Engineer looking to work on complex data challenges ...

engagement, and the optimisation of existing reporting solutions. Key responsibilities include: Enhancing and maintaining existing Power BI dashboards and reporting solutions Developing and supporting semantic models and data layers that underpin reporting Translating business requirements into scalable reporting and data models Working closely with stakeholders to understand reporting needs … Skills & Experience You will bring strong commercial experience in: Power BI development across both front-end reporting and back-end modelling Data modelling and semantic layer design SQL for data querying and transformation DAX development and performance optimisation Stakeholder engagement and requirements gathering Communicating technical concepts ...

teams who use curated data for model development, and the team that administers the underlying cloud infrastructure. The Data Engineer makes sure the data layer serves each of these groups well, so that none of them has to rebuild it for their own use. What This Role Does … data science and AI teams to make sure the data meets their requirements for quality, freshness, and structure. The Data Engineer contributes to the semantic layer that gives AI and analytics consumers consistent, well-defined access to business metrics and entities, and keeps data lineage and governance ...

complex business problems through data, from understanding requirements to delivering analytical solutions . Translate business needs into clear and scalable data models and our semantic layer , ensuring technical solutions align with our long-term platform design and methodologies . Build and maintain robust data transformations and models ...

looking for a Senior Data Analytics Engineer to own the analytics layer and become the main point of contact for data across the business. You’ll work closely with Product, Marketing, Finance and Operations to understand their data requirements, turn them into reliable models and metrics, agree priorities … also support the Data Analyst in working confidently with the data. You’ll be joining an established data platform with the ingestion layer already in place. Your focus will be on the modelling, analytics and reporting layer built on top of it. What You’ll Own Data Modelling ...

loss ratio, so we understand the risk and commercial impact of what we ship, not just conversion Own metric definitions and contribute to our semantic layer, helping ensure the business works from a consistent version of each number Collaborate with BI and Data Engineering colleagues on analytical ...

vision and hands-on execution of our next-generation Object-Centric Data Fabric . You will transition traditional application-centric architectures into a centralised semantic layer that seamlessly unifies multi-stream operational data—including Electronic Data Capture (EDC), patient telemetry, and real-world health datasets. In this role … optimisation, and regulatory documentation. This allows you to focus on driving high-impact platform architecture. Data Fabric & Lake Architecture: Architect and evolve the enterprise semantic data fabric, converting multi-stream clinical execution datasets into an object-centric model. Design and execute a modern Data Lake strategy centred on Apache ...

standard use cases. Design data ingestion architecture (batch, micro-batch, and streaming) with clear boundaries for system-to-system integration. Define architecture for the semantic layer and self-serve analytics infrastructure. Provide input to data squads for complex data products and support Data Product Managers and Data Engineers … platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g.,SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions). Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions. Provide architectural input to vendor and tooling decisions ...

e.g. Consumer Duty, CASS, KYC/AML, GDPR) into concrete data controls, monitoring and reporting. Maintain and evolve the analytics glossary, data catalogue and semantic layer so compliance-related metrics are clearly defined, consistent and auditable. Support internal and external audit requests with well-documented, reproducible analysis. Modern … Dashboards Build and maintain dashboards and reports using modern BI tools. Ensure metrics are correctly defined, documented, and consistent with the data catalogue and semantic layer. As the role broadens, support wider analytics team with ad hoc analysis outside governance and compliance. Data Quality & Documentation Work with the Chief ...

rituals that make this routine. Define the analytical data model: entity and event design that joins consistently across product flows, slowly changing dimensions, a semantic layer, and metric definitions. Introduce data contracts and governance standards with Tech and Data Engineering, so that new events and tables are designed ...

bind every Data Product: metadata and data contract specifications, output port and schema design, data product versioning, DQ requirements, SLA and SLO declarations, and semantic layer conventions Champion data quality, lineage, observability and governance, ensuring checks, SLAs and alerting are expressed as code and monitored in production rather ...

bind every Data Product: metadata and data contract specifications, output port and schema design, data product versioning, DQ requirements, SLA and SLO declarations, and semantic layer conventions Champion data quality, lineage, observability and governance, ensuring checks, SLAs and alerting are expressed as code and monitored in production rather ...

/Dagster), and manage IaC via Git and CI/CD pipelines Connect disparate datasets into well-managed data products, contributing to platform migration, semantic layers, and automation Own data quality, validation, reconciliation, automated failure detection, and schema validation Deliver changes to SOx-relevant data assets with change management ...

challenge assumptions, identify opportunities and influence strategic decisions. Key Responsibilities: Lead the design and governance of modern data warehouses, data lakes, lakehouse platforms, semantic layers, dimensional models, master data strategies and analytics ecosystems. Architect cloud-native data platforms—particularly Snowflake—covering performance, workload management, security, access controls, cost governance … Deep expertise in modern data architectures, including data warehouses, data lakes, lakehouse platforms and analytics ecosystems. Extensive experience in enterprise and dimensional data modelling, semantic layers, master data strategies and data governance frameworks. Strong understanding of data product thinking and the creation of scalable, reusable and business-oriented models ...

credentials and adjacent platform experience will be considered. The Work Architecture & Design Design and document multi-agent architecture blueprints, agentic orchestration patterns, knowledge and semantic layer blueprints, AI governance blueprints, and AgentOps/LLMOps architecture Design the knowledge architecture underpinning agent intelligence: embeddings pipelines, vector retrieval, and semantic search — structured around commerce-specific intent, product relationships, and category hierarchies Architect the integration layer connecting agentic systems to enterprise commerce stacks (OMS, PIM, DAM, CRM, payments, pricing, fulfilment) via API gateways, event buses, and emerging agentic protocols (MCP, A2A, ACP, UCP) Lead build vs. buy decisions across ...

numbers people can act on. What the role involves dbt on BigQuery, day to day. Model design, data quality, the source-of-truth layer, and every change that lands in it. Joining the business together across systems. Our CRM, ledgers, operational tools, and compliance systems each hold part … keys and different definitions. Resolving them into one coherent model is central to the role. Leading our Lightdash to Omni migration , then owning the semantic layer and everything built on it. Regulatory and compliance reporting. Recurring submissions and the models behind them, against externally fixed deadlines. Partnering with ...