6 of 6 Dimensional Modelling Jobs in East London

including Azure Databricks, SQL Database, Data Factory, and T-SQL. In-depth understanding of London Market insurance data and Actuarial/Finance business processes. Experience with ETL processes, data modelling, and dimensional modelling techniques. Proficient with Azure DevOps, CI/CD, GIT, and deployment strategies. Proven track record in delivering cloud-based enterprise data solutions and supporting More ❯

depth knowledge of Snowflake architecture, features, and best practices. · Experience with CI/CD pipelines using Git and Git Actions. · Knowledge of various data modeling techniques, including Star Schema, Dimensional models, and Data Vault. · Hands-on experience with: · Developing data pipelines (Snowflake), writing complex SQL queries. · Building ETL/ELT/data pipelines. · Kubernetes and Linux containers (e.g., Docker More ❯

and emerging technologies. What You’ll Bring ✅ Extensive hands-on experience with Databricks , and Microsoft Azure data tools (must-have: Azure Data Factory, Azure Synapse, or Azure SQL). ✅ Dimensional modelling expertise for analytics use cases. ✅ Strong ETL/ELT development skills. ✅ Python scripting experience for data automation. ✅ Experience with CI/CD methodologies for data platforms. ✅ Knowledge More ❯

Business Intelligence Engineer Hybrid – London Up to £450 a day Inside IR35 6 Months Key Skills: Business Intelligence (Data modelling, data warehousing, Dashboarding) SQL & Python AWS (S3, Lambda, Glue, Redshift) The Senior Business Intelligence Engineer occupies a unique role at the intersection of technology, marketing, finance, statistics, data mining, and social science. We provide the key insight into customer … using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills: - Strong analytical and problem-solving abilities - Excellent understanding of dimensional modeling and star schema design (Facts, dimensions, scd type 2) - Experience with agile development methodologies - Strong communication skills and ability to work with cross-functional teams - Background in data More ❯

capabilities, they are evolving toward a clearer separation between Data Engineering, Analytics Engineering, and Data Product disciplines. This role will sit firmly in the Analytics Engineering function, focused on modelling and building the semantic layer that powers consistent, reliable insights across the company’s BI and data science platforms. This role will focus on the “middle layer", designing dimensional … other downstream consumers. Work closely with Data Engineers responsible for ingestion (from source systems to raw layers such as S3 or cloud storage), but focus your efforts on the modelling and transformation stage. Collaborate with the Data Product team to ensure the semantic layer serves evolving business and analytical needs. Support best practices in CI/CD (using GitHub … maintaining dbt pipelines. Contribute to a common, reusable data model that serves BI, Data Science, and AI/ML teams alike. Required Skills & Experience: Strong experience with SQL and dimensional modelling in dbt. Proven experience building and maintaining semantic layers in modern data platforms. Familiarity with Medallion architecture, CI/CD processes (GitHub), and version-controlled data workflows. More ❯

using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills: - Strong analytical and problem-solving abilities - Excellent understanding of dimensional modeling and star schema design (Facts, dimensions, scd type 2) - Experience with agile development methodologies - Strong communication skills and ability to work with cross-functional teams - Background in data More ❯