7 of 7 Contract 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 ❯

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 ❯

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 ❯