8 of 8 Kimball Methodology Jobs in the North of England

Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB • Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have) • Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of other data tools and programming languages such as Python & Spark and Strong SQL experience. More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms More ❯

Build and maintain key artefacts: ER models, data dictionaries, pipeline/lineage models Own architecture decisions and guide clients through change approval processes Champion governance and modelling standards (Kimball, warehousing best practices) Analyse source data, evaluate APIs, reverse-engineer data models Work closely with engineers to deliver cloud-based data solutions Visualise insights via tools like Power BI More ❯

Product Owners, Test Analysts, and BI Teams. Skills & Experience: * Proficiency in Azure tools (Data Factory, Databricks, Synapse, etc.). * Strong SQL and experience with data warehousing (Kimball methodology). * Programming skills in Python, Scala, or PySpark. * Familiarity with Power BI, SharePoint, and data integration technologies. * Understanding of DevOps, CI/CD, and cloud concepts (IaaS, PaaS, SaaS More ❯

You Experience with finance/financial systems and concepts Azure Databricks Azure Data Factory Excellent SQL skills Good Python/Spark/pyspark skills Experience of Kimball Methodology and star schemas (dimensional model). Experience of working with enterprise data warehouse solutions. Experience of working with structured and unstructured data Experience of a retail environment preferred A More ❯

and evolve enterprise-wide data models across key domains like Product, Customer, Supply, Finance, and Location Apply Kimball dimensional modelling for consumption layer design and Data Vault methodology for raw and business layer integration Define and maintain data architecture principles, patterns, and standards Collaborate with data platform teams on governance, quality, lineage, and optimisation Consult with squads … to a Data Product Ownership model, enabling domain-aligned teams What youll bring to this role Proven experience in enterprise data architecture in a complex organisation Expertise in Kimball and Data Vault 2.0 methodologies Strong grasp of data modelling, metadata, and governance knowledge Hands-on experience with modern data platforms (Databricks, Delta Lake, Unity Catalog, Azure) Ability to More ❯

multiple business domains. The Data Architect will be responsible for designing and evolving data models across raw, business and consumption layers, applying best-in-class methodologies such as Kimball and Data Vault 2.0. You'll help define and drive architecture principles, ensure alignment across squads, and collaborate closely with data platform teams to improve data governance, quality, lineage … the chance to influence strategy and shape long-term data capabilities. Data Architect - Key Requirements: Strong background in enterprise data architecture within complex environments Hands-on expertise with Kimball and Data Vault 2.0 methodologies Experience designing models across raw, business, and consumption layers Solid understanding of metadata, cataloguing, and data governance practices Working knowledge of modern data platforms More ❯