26 to 37 of 37 Dimensional Modelling Jobs

engineering solutions. The Fabric Ecosystem: Demonstrable, hands-on expertise with Microsoft Fabric , SQL , and Python/PySpark Notebooks . Core Competencies: Proven skill in dimensional modeling, data governance, and data extraction from online platforms via SaaS and APIs. Analytical Mindset: Excellent ability to analyze, manipulate, and interpret complex business ...

combining business analysis, data analysis and data cataloguing to identify and document data requirements. Proficient use of enterprise data platforms, semantic models and dimensional modelling (star schemas, fact/dimension tables). Proficient in data architecture principles, ETL processes and data pipeline concepts. Experience with data cataloguing tools ...

within a fast-paced environment. Desirable Skills Previous experience within the insurance, financial services or other regulated industries. Understanding of data warehousing concepts and dimensional modelling. Exposure to Python or R for data analysis. Knowledge of data governance and data quality best practices. Experience working within Agile environments. Package ...

Fabric Integrate and transform Salesforce data into a unified data platform. Develop and optimise ETL/ELT processes for performance and scalability. Implement data modelling best practices (star schema, dimensional modelling). Collaborate with stakeholders to translate business requirements into technical solutions. Key Requirements Proven experience ...

Fabric Integrate and transform Salesforce data into a unified data platform. Develop and optimise ETL/ELT processes for performance and scalability. Implement data modelling best practices (star schema, dimensional modelling). Collaborate with stakeholders to translate business requirements into technical solutions. Key Requirements Proven experience ...

Fabric Integrate and transform Salesforce data into a unified data platform. Develop and optimise ETL/ELT processes for performance and scalability. Implement data modelling best practices (star schema, dimensional modelling). Collaborate with stakeholders to translate business requirements into technical solutions. Key Requirements Proven experience ...

Agentic AI. Strong experience Must have prior experience with end-to-end implementation of Cloud data technologies (i.e.Fabric, Snowflake). Expertise in data modelling, ELT and implementing complex stored Procedures. Expertise in various Snowflake technologies like Snowpark, SnowPipe, SnowPipe Stream, Dynamic Tables, Document AI, Cortex Analytics, Unistore etc. Expertise … systems, Salesforce, GIS, PI Historian to Snowflake. Deep understanding of relational as well as NoSQL data stores, methods, and approaches (star and snowflake, dimensional modelling and third normal form) Experience with data security and data access controls and design Deep understanding of SoX, GDPR and Regulatory/ ...

Data Modeller London Up to £65,000 + benefit This is an opportunity to join a growing data function where modelling expertise is a key priority. You will play a central role in shaping data foundations while being supported on a clear pathway into Data Architecture, with exposure … collaborative and well established, with a clear focus on improving data quality, consistency, and accessibility. You will join a team that values strong modelling standards and best practice. The Role Develop and maintain conceptual, logical, and physical data models across a range of business domains Support and promote data ...

Collaborate with operational teams to identify and surface key data for dashboards. Develop and implement data validation checks and quality control measures. Assist in modelling and structuring data in the new system for optimal visualisation. Provide technical expertise to enhance data reliability, traceability, and overall quality. Essential Skills … Experience : Strong experience with Snowflake and Data Warehousing. Proficiency in SQL and Azure Data Factory. Familiarity with data flows, dimensional modelling, and Power BI. BA background highly advantageous. Knowledge of KQL and DAX is desirable. Desirable Attributes : Experience in a regulated industry or with investment/financial data. ...

impact Analytics Engineer role within a purpose-driven organisation at a pivotal stage of its data journey. You will take ownership of critical data modelling work within a modern cloud environment, helping to stabilise and scale key data pipelines while contributing to meaningful, real-world outcomes. ROLES AND RESPONSIBILITIES … Analytics Engineer will: Own and deliver in-flight data modelling projects, ensuring continuity and completion Design and maintain dbt models including fact tables, dimensions, and metric layers Support and optimisie critical data pipelines, particularly around billing and reporting workflows Collaborate closely with data engineers to manage data flows across ...

ingest and transform data from multiple sources. Apache Airflow for workflow orchestration, scheduling and automation. Azure SQL and cloud-based data platforms. Data modelling, warehousing and optimisation activities. Data quality, governance and validation processes. Power BI reporting and business intelligence requirements. Technical and non-technical stakeholders across the business. … integration. Python scripting for automation, transformation and data engineering tasks. Experience with Apache Airflow or similar orchestration tools. Understanding of data warehousing and data modelling principles, including dimensional modelling. Experience working with cloud-based data platforms. Familiarity with Git and version control practices. Strong communication skills ...

data solutions \nStrong proficiency in Databricks, SQL, and Python/PySpark, including building, optimizing, and troubleshooting ETL pipelinesExperience designing scalable, maintainable data architectures and dimensional models for BI, reporting, and analytical use casesProven ability to partner with business stakeholders to gather requirements, shape solutions, and communicate effectivelyStrong understanding … ecosystemManage ETL orchestration, dependencies, and deployments to ensure reliability and operational stabilityMonitor production performance and resolve root causes to prevent recurring data delivery issuesApply dimensional modeling and support Unified Star Schema development to ensure semantic consistencyMentor and coach junior engineers while promoting strong technical standards and collaborative ways ...