1 to 25 of 83 Dimensional Modelling Jobs in the UK

or centralisation. Identify and cultivate relationships with key data creators, data owners and data consumers. Ensure data assets are properly defined and maintained within a central data catalogue. Data modelling to transform operational data into analytic/reporting structures such as Kimball style multi-dimensional models. Take ownership of data issues through to resolution, working with IT and …/dashboards that can be easily understood and used. Locate and define new data-related process improvement opportunities. Skills and Experience: Essential: • Experience managing/leading a team. • Data modelling, cleansing and enrichment, with experience in conceptual, logical, and physical data modelling. • Familiarity with data warehouses and analytical data structures. • Experience of data quality assurance, validation, and lineage. • Knowledge … Git or other source control software. • Knowledge of Orchestration Tools and processes (e.g SSIS, Data Factory, Alteryx) • Power BI Development including the data model, DAX, and visualizations. • Relational and Dimensional (Kimball) data modelling • Proficiency in SQL (T-SQL, PL/SQL, Databricks SQL) Desirable: • Databricks (or Alternative Modern Data Platform such as Snowflake) • Experience working in a regulated More ❯

Azure Synapse) and architecting cloud-native data platforms. Programming Proficiency: Expert-level skills in Python (PySpark) and SQL for data engineering and transformation. Scala is a strong plus. Data Modelling: Strong understanding and practical experience with data warehousing, data lake, and dimensional modelling concepts. ETL/ELT & Data Pipelines: Proven track record of designing, building, and optimizing More ❯

Azure Synapse) and architecting cloud-native data platforms. Programming Proficiency: Expert-level skills in Python (PySpark) and SQL for data engineering and transformation. Scala is a strong plus. Data Modelling: Strong understanding and practical experience with data warehousing, data lake, and dimensional modelling concepts. ETL/ELT & Data Pipelines: Proven track record of designing, building, and optimizing More ❯

Azure Synapse) and architecting cloud-native data platforms. Programming Proficiency: Expert-level skills in Python (PySpark) and SQL for data engineering and transformation. Scala is a strong plus. Data Modelling: Strong understanding and practical experience with data warehousing, data lake, and dimensional modelling concepts. ETL/ELT & Data Pipelines: Proven track record of designing, building, and optimizing More ❯

and performance tuning. Solid experience with Python , ideally using PySpark in Azure Databricks . Hands-on experience with Azure Data Lake Storage Gen2 . Understanding of data warehouse concepts , dimensional modelling , and data architecture . Experience working with Delta Lake and large-scale data processing. Experience building ETL pipelines in Azure Data Factory or similar orchestration tools. Familiarity More ❯

them with robust data pipelines. DESIRABLE LANGUAGES/TOOLS Proficiency in programming languages such as Python, Java, Scala, or SQL for data manipulation and scripting. Strong understanding of data modelling concepts and techniques, including relational and dimensional modelling. Experience in big data technologies and frameworks such as Databricks, Spark, Kafka, and Flink. Experience in using modern data architectures More ❯

experience working with Fabric-based solutions. Azure Ecosystem: At least 2 years of experience delivering business solutions using: Azure Data Factory/Synapse Power BI Azure SQL Server Data Modelling: Strong knowledge of dimensional modelling (Kimball). Familiarity with other techniques such as Data Vault 2.0. Development Experience: Minimum 3 years in database and/or analytics More ❯

They closely collaborate with data scientists, analysts, and software engineers to ensure efficient data processing, storage, and retrieval for business insights and decision-making. From their expertise in data modelling, ETL (Extract, Transform, Load) processes, and big data technologies it becomes possible to develop robust and reliable data solutions. RESPONSIBILITIES Data Pipeline Development: Design, implement, and maintain scalable data … in software engineering a plus. DESIRABLE LANGUAGES/TOOLS Proficiency in programming languages such as Python, Java, Scala, or SQL for data manipulation and scripting. Strong understanding of data modelling concepts and techniques, including relational and dimensional modelling. Experience in big data technologies and frameworks such as Databricks, Spark, Kafka, and Flink. Experience in using modern data architectures More ❯

design and deliver scalable data products that enable self-service analytics using Snowflake, Power BI, Python, and SQL. What You’ll Do: Build robust ETL/ELT pipelines and dimensional models for analytics Enforce data quality, security, and governance in a Data Mesh setup Enable self-service insights through intuitive data models and training Own data products end-to … continuous improvement Promote innovation and best practices across the organisation What We’re Looking For: Strong skills in SQL and Power BI. Python is beneficial Solid experience with data modelling and ETL pipelines Knowledge of cloud environments – Azure Experience with Snowflake and Databricks Familiarity with data governance in decentralised environments Excellent communication and stakeholder engagement skills A proactive, problem 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Data Lakehouse Medallion architecture Microsoft Azure T-SQL Development (MS SQL Server 2005 onwards) Python, PySpark Experience of the following systems would also be advantageous: Azure DevOps MDS Kimball Dimensional Modelling Methodology Power Bi Unity Catalogue Microsoft Fabric Experience of the following business areas would be advantageous: Insurance sector (Lloyds Syndicate, Underwriting, Broking) Qualifications: Degree educated in relevant More ❯

SQL Server) Qualifications Desired qualifications and experience: Experience with Programming languages such as (Python, SQL etc.) Experience building and maintaining data pipelines. Familiarity with medallion architecture. An understanding of dimensional modelling concepts. Proficiency with reporting tools, preferably Power BI. Practical experience working in an Agile Scrum environment. At Solus, we offer a collaborative and innovative work environment where More ❯

with MS SQL Server , T-SQL , and performance tuning for reporting workloads. An understanding of SSRS and SSIS for traditional reporting and ETL processes. Data Warehousing Concepts : Understanding of dimensional modeling, fact and dimension tables. Solid understanding of data visualisation principles and dashboard design best practices. Familiarity with Azure DevOps version control for Power BI and SQL development. Performance More ❯

with MS SQL Server , T-SQL , and performance tuning for reporting workloads. An understanding of SSRS and SSIS for traditional reporting and ETL processes. Data Warehousing Concepts : Understanding of dimensional modeling, fact and dimension tables. Solid understanding of data visualisation principles and dashboard design best practices. Familiarity with Azure DevOps version control for Power BI and SQL development. Performance More ❯

About the Platform: This greenfield initiative is focused on building a next-gen data ecosystem with a tech stack including: Snowflake for cloud data warehousing dbt for transformation and modelling Azure for cloud infrastructure and orchestration Fivetran for automated data ingestion Power BI and other modern BI tools for reporting and visualisation 🧠 What You’ll Do: Design and implement … BI developers to deliver insightful, high-performance dashboards Work with Data Engineers to optimise data ingestion and orchestration pipelines using Azure Data Factory and Fivetran Apply best practices in dimensional modelling, layered architecture, and data quality ✅ What We’re Looking For: Strong experience in data modelling and SQL Hands-on experience with dbt and cloud data platforms … like Snowflake or Azure Synapse Analytics Solid understanding of modern data stack principles , including layered modelling and data warehouse design Excellent communication skills and the ability to work with stakeholders across technical and non-technical teams Nice to have: Experience with Power BI or similar BI tools Familiarity with CI/CD practices in data environments Exposure to data More ❯