19 of 19 Kimball Methodology Jobs in London

complex Data Programmes Strong Data Modelling experience (especially Conceptual Data Models) Demonstrable background in Data Engineering Design processes (ETL, ELT), with good knowledge of Data Vault, Inmon and Kimball Strong knowledge of MS Azure stack (including Data Factory (ADF), Data Lake Storage, SQL, Azure ML and Power BI) Proven experience with Snowflake Architecture, including DevOps integration and CI More ❯

complex Data Programmes Strong Data Modelling experience (especially Conceptual Data Models) Demonstrable background in Data Engineering Design processes (ETL, ELT), with good knowledge of Data Vault, Inmon and Kimball Strong knowledge of MS Azure stack (including Data Factory (ADF), Data Lake Storage, SQL, Azure ML and Power BI) Proven experience with Snowflake Architecture, including DevOps integration and CI More ❯

attending workshops, possibly across differ locations if needed) Nice to have: Demonstrable background in Data Engineering Design processes (ETL, ELT), with good knowledge of Data Vault, Inmon and Kimball Insurance industry experience, with good understanding of what a claim is, claims process(es) etc Previous work on Data strategies Exposure to collaborative modelling tools such as Ellie.ai Immediate More ❯

impact analytical products. Design, build, and maintain Power BI dashboards that inform strategic business decisions. Use PySpark , Databricks or Microsoft Fabric , and relational/dimensional modelling (Kimball methodology) to structure and transform data. Promote best practices in Git , CI/CD pipelines (Azure DevOps), and data governance. Lead the rollout, adoption, and training of dashboards and data … operations teams. What We're Looking For 3 to 5 years of experience in data analysis, BI development, or data engineering. Strong knowledge of relational and dimensional modelling (Kimball or similar). Proven experience with: Power BI (advanced DAX, data modelling, RLS, deployment pipelines) PySpark and Databricks or Microsoft Fabric Git and CI/CD pipelines (Azure DevOps More ❯

management position. Financial services experience is essential , ideally covering lending, servicing, or securitisation data. Deep technical expertise in Microsoft and Azure data technologies. Strong knowledge of data modelling (Kimball) , ETL/ELT , and hybrid cloud architectures . Proven ability to drive quality, governance, and best practices within engineering teams. Excellent communication, stakeholder management, and leadership skills. If you More ❯

Hands-on experience with Azure (ADF, Synapse, Data Lake) or AWS/GCP equivalents. Familiarity with scripting languages (Python, PySpark). Knowledge of data modelling and warehouse design (Kimball, Data Vault). Exposure to Power BI to support optimised data models for reporting. Agile team experience, CI/CD familiarity, Git workflows. If this sounds like you, apply More ❯

documentation). Apache Airflow (DAG design, operators, scheduling, dependencies). Databricks (Spark, SQL, Delta Lake, job clusters, SQL Warehouses). Strong SQL skills and understanding of data modeling (Kimball, Data Vault, or similar) . Proficiency in Python for scripting and pipeline development. Experience with CI/CD tools (e.g., GitHub Actions, GitLab CI, Azure DevOps). Familiarity with More ❯

both technical and non-technical stakeholders. Extensive experience of data modelling to at least 3NF Strong knowledge of database structure systems and data mining Proficient in Kimball methodology and Data Vaults Deep understanding of database fundamentals and experience in designing metadata-driven ingestion and transformation pipelines. Experienced in Master Data Management (MDM), data cataloguing, and managing data More ❯

and Azure-based architecture , with a strong ability to translate complex requirements into robust technical solutions. Key Responsibilities Design and implement conceptual, logical, and physical data models (3NF, Kimball, Data Vault) Architect and optimise data platforms including data lakes , lakehouses , and data warehouses Lead the development of metadata-driven ingestion and transformation pipelines Ensure compliance with GDPR and More ❯

and Azure-based architecture , with a strong ability to translate complex requirements into robust technical solutions. Key Responsibilities Design and implement conceptual, logical, and physical data models (3NF, Kimball, Data Vault) Architect and optimise data platforms including data lakes , lakehouses , and data warehouses Lead the development of metadata-driven ingestion and transformation pipelines Ensure compliance with GDPR and More ❯

technical skills that will include - SQL, SSIS, SSRS, SAS, Power BI, Power Platform, Azure Data Factory, Azure Data Lake, Databricks A good understanding of dimensional modelling techniques, including Kimball's Business Development Lifecycle Ability to design hybrid data solutions across on-prem and cloud data sources Expert with data engineering tools and automation techniques This is a great More ❯

warehousing concepts and best practices. Experience of, and ability to, transform raw transactional data into well-structured analytics-ready datasets using schemas like the star schema (Kimball methodology) Data Quality & Governance : build trust in data by implementing data validation checks, testing frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but More ❯

warehousing concepts and best practices. Experience of, and ability to, transform raw transactional data into well-structured analytics-ready datasets using schemas like the star schema (Kimball methodology) Data Quality & Governance : build trust in data by implementing data validation checks, testing frameworks, and clear documentation within your pipelines Experience in the following areas is not essential but More ❯

What We're Looking For Extensive experience in data architecture and modelling. Strong knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2 More ❯

What We're Looking For Extensive experience in data architecture and modelling. Strong knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2 More ❯

context and operational needs. Qualifications & Skills Technical Expertise Proven hands-on experience with data platforms such as Azure, AWS, and Informatica. Strong knowledge of data modelling techniques (e.g., Kimball, Star Schema, Data Vault). Proficiency with cloud-native and DataOps solutions (Azure/AWS stack, event streaming with Azure Event Hubs, Kafka). Experience in Big Data solutions More ❯

context and operational needs. Qualifications & Skills Technical Expertise Proven hands-on experience with data platforms such as Azure, AWS, and Informatica. Strong knowledge of data modelling techniques (e.g., Kimball, Star Schema, Data Vault). Proficiency with cloud-native and DataOps solutions (Azure/AWS stack, event streaming with Azure Event Hubs, Kafka). Experience in Big Data solutions More ❯

context and operational needs. Qualifications & Skills Technical Expertise Proven hands-on experience with data platforms such as Azure, AWS, and Informatica. Strong knowledge of data modelling techniques (e.g., Kimball, Star Schema, Data Vault). Proficiency with cloud-native and DataOps solutions (Azure/AWS stack, event streaming with Azure Event Hubs, Kafka). Experience in Big Data solutions More ❯

context and operational needs. Qualifications & Skills Technical Expertise Proven hands-on experience with data platforms such as Azure, AWS, and Informatica. Strong knowledge of data modelling techniques (e.g., Kimball, Star Schema, Data Vault). Proficiency with cloud-native and DataOps solutions (Azure/AWS stack, event streaming with Azure Event Hubs, Kafka). Experience in Big Data solutions More ❯