17 of 17 Dimensional Modelling Jobs in Central London

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

central Data Platform, working closely with the Data Management Team. Analysis of normalised transactional data and analytic data sources. Analysis of semi structured and file-based data extracts. Data modelling to transform operational data into analytic/reporting structures such as Kimball style multi-dimensional models. Essential Skills for the Data Analyst: Proven Data Analyst experience of at … least 5 years, within a Financial Services environment, with particular emphasis on Risk or cross asset derivatives areas. Data modelling, cleansing and enrichment, with experience in conceptual, logical and physical data modelling and data cleansing and standardisation. Familiarity with Data warehousing and analytical data structures. Data quality assurance, validation and linkage. Experience creating BI models and dashboards, ideally More ❯

central Data Platform, working closely with the Data Management Team. Analysis of normalised transactional data and analytic data sources. Analysis of semi structured and file-based data extracts. Data modelling to transform operational data into analytic/reporting structures such as Kimball style multi-dimensional models. Essential Skills for the Data Analyst: Proven Data Analyst experience of at … least 5 years, within a Financial Services environment, with particular emphasis on Risk or cross asset derivatives areas. Data modelling, cleansing and enrichment, with experience in conceptual, logical and physical data modelling and data cleansing and standardisation. Familiarity with Data warehousing and analytical data structures. Data quality assurance, validation and linkage. Experience creating BI models and dashboards, ideally More ❯

looking for: Strong commercial experience in BI/Data Warehousing Proven expertise with Power BI and SQL (DAX, T-SQL) Experience with cloud platforms (ideally Azure) Solid understanding of dimensional modelling and ETL processes Excellent communication and stakeholder management skills 💼 Why this role? Outside IR35 – keep more of your day rate Hybrid flexibility with a vibrant central London More ❯

transformation logic, and uploading data in target tables. You would be responsible for designing, testing, and troubleshooting the company's data storage system before it goes live. Knowledge of dimensional modeling and data warehouse concepts, such as star schemas, snowflakes, dimensions, facts Define scope, execution plans, and coordinate test activities Ensure all sign-offs on deliverables (overall test strategy 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 ❯

/Experience Degree level qualified or equivalent. SQL Programming. C# Software development. Knowledge and Skills C# Programming to high level of proficiency. Software analysis and design. SQL query language. Dimensional modelling Data warehouse design concepts, (Inmon or Kimball) The Client is a Bank based in the City of London. This is a 2 year FTC position with a More ❯