17 of 17 Dimensional Modelling Jobs in the City of 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 ❯

including scheduling, monitoring, and alerting. Collaborate with cross-functional teams (Product, Engineering, Data Science, Compliance) to define data requirements and build reliable data flows. Champion best practices in data modelling, governance, and DevOps for data engineering (CI/CD, IaC). Serve as a key communicator between technical teams and business stakeholders, translating complex data needs into actionable plans. … Snowflake, BigQuery, Redshift). Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Snowflake, Power BI, Python, and SQL. Your work will enable self-service analytics and support data governance across the business. Key Responsibilities: Develop robust ETL/ELT pipelines and dimensional models for BI tools Define and implement data quality, ownership, and security standards Empower business teams with intuitive, self-serve data models Own data products end-to-end, from … design to continuous improvement Promote innovation and best practices in data engineering About You: Strong experience with SQL, Python, and BI tools (e.g., Power BI) Solid understanding of dimensional modelling and data architecture Experience working in governed, decentralised data environments Excellent communication and stakeholder engagement skills Analytical mindset with a focus on delivering business value If you are 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 ❯

in SQL and Python for data transformation and workflow automation Experience with AWS data tools (e.g. Redshift, Glue, Lambda, S3 ) and infrastructure tools such as Terraform Understanding of data modelling concepts (e.g. dimensional models, star/snowflake schemas) Knowledge of data quality, access controls , and compliance frameworks Nice to Have Experience with orchestration or pipeline frameworks like Airflow More ❯

Databricks, Azure SQL, and Data Factory. Deep technical knowledge of SQL Server including stored procedures and complex data transformation logic. Proven experience in designing and delivering data warehousing and dimensional modelling solutions. Excellent collaboration skills with a track record of working in Agile teams. Experience with Azure DevOps, GIT, and CI/CD pipelines. Comfortable liaising directly with 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 ❯

Microsoft Azure ecosystem Exposure to or interest in: Microsoft Fabric and its evolving role in enterprise data platforms Azure DevOps for CI/CD and deployment T-SQL and dimensional modelling (Kimball methodology) Experience in Financial Services or Lloyd's market is a plus Apply now or get in touch to find out more - alexh@pioneer-search.com More ❯

data visualization platforms. Demonstrable experience planning and executing complex reporting & analytics projects across multiple stakeholders. Understanding of data quality frameworks and importance of availability of reliable data Knowledge of dimensional modelling and experience Strong analytical thinking and problem-solving skills with the ability to interpret complex data and provide actionable insights. Curiosity and willingness to explore complex and 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 ❯

SQL to create scalable, intuitive data solutions that drive business value. Key Responsibilities Build Data Products: Collaborate with business domains to design and develop ETL/ELT pipelines and dimensional models optimised for Power BI Drive Governance: Define and enforce data ownership, quality, and security standards within the Data Mesh architecture Enable Self-Service: Create intuitive data models and … and collaboration. You should bring: Technical Expertise: Proven experience coding ETL/ELT pipelines with Python, SQL, or ETL tools, and proficiency in Power BI, Tableau, or Qlik Data Modelling Skills: Strong knowledge of dimensional modelling and database principles Governance Experience: Track record of working in democratized data environments, establishing controls and guardrails Collaboration & Communication: Ability to More ❯

or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. Expertise in Microsoft Azure is mandatory including components like Azure Data Factory, Azure More ❯

or Data-Warehouse projects, across technologies used in the enterprise space. Software development experience using: Object-oriented languages (e.g., Python, PySpark,) and frameworks Stakeholder Management Expertise in relational and dimensional modelling, including big data technologies. Exposure across all the SDLC process, including testing and deployment. Expertise in Microsoft Azure is mandatory including components like Azure Data Factory, Azure More ❯

involves building strong relationships across the business to support existing systems and contribute to future upgrades and system improvements. Key Responsibilities: Design, develop, and test data warehouse (Star schema dimensional model), reporting, and dashboard solutions (SSRS/Power BI). Create, maintain, and enhance data integrations (IntApp Integrate/SSIS). Analyse database data to identify and fix integrity More ❯

Job Description AWS Stack, data being landed in S3, Lambda triggers, Data Quality, data written back out to AWS S3(Parquet Formats), Snowflake for dimensional model. Design and build the data pipelines, work with someone around understanding data transformation, this is supported by BA's, building out the data pipelines, moving into layers in the data architecture (Medallion architecture More ❯