1 to 25 of 158 Dimensional Modelling Jobs

and business intelligence tools to support decision-making, performance tracking, and regulatory needs across corporate functions. Implement and maintain robust data models across key domains using best practices in dimensional modeling, normalization, and semantic layering. Standardize data acquisition, onboarding, ingestion, transformation and distribution frameworks globally to optimize scalability, open architecture and delivery speed. Support the implementation of data governance More ❯

the mobile/telecoms industry would be a bonus! Key outputs for the role • Design, build, and maintain scalable and trustworthy data models in dbt, making use of Kimball Dimensional and One Big Table (OBT) methodologies. • Translate business requirements from stakeholders into robust, well-documented and tested dbt models. • Develop and own workflows within Google Cloud Platform environments, primarily … and implement robust, well-documented and performant dbt models that serve as a single source of truth for business reporting. • Implement and champion data quality testing, documentation standards, and modelling best practices within dbt projects. • Troubleshoot and resolve any issues or errors in the data pipelines. • Stay updated with the latest cloud technologies and industry best practices to continuously … be expecting to see: • Expert level proficiency in SQL. • Deep, practical experience of building and architecting data models with dbt. • A strong understanding of data warehousing concepts and data modelling techniques (e.g., Kimball, Dimensional Modelling, One Big Table). • Solid, hands-on experience within the Google Cloud Platform, especially with BigQuery. • Proven experience working directly with business More ❯

critical in the development and support of the new Evelyn Data Platform, which is being engineered on Snowflake, utilising Azure Data Factory pipelines for data integration, dbt for data modelling, Azure BLOB Storage for data storage, and GitHub for version control and collaboration. The role will be working in an agile and collaborative environment within a growing and skilled … ADF) and GitHub, for ETL development. • Experience building and maintaining reports using SQL Server Reporting Services (SSRS). • Solid understanding of data warehousing concepts, including star/snowflake schemas, dimensional modelling, and data vault 2.0, and of the principles of ETL technical design • Experience with SQL Server Analysis Services (SSAS) is a plus. • Familiarity with data visualization tools More ❯

Operational, and Finance functions through robust, scalable, and innovative data solutions. In this position, you'll be responsible for designing, building, and optimizing data warehouses using best practices in dimensional modelling, Kimball methodologies, star schema design, and Data Vault principles, ensuring adherence to sound data architecture practices. Based in Avonmouth on a hybrid working basis – 2 days in … Lead optimization efforts in Power BI, leveraging Power BI Premium features such as incremental refresh, paginated reports, and composite models to enhance reporting performance and scalability. DAX and Data Modelling: Write advanced DAX and perform complex data modelling within Power BI to support high-quality, dynamic reporting. Self-Service BI: Empower stakeholders to build their own reports and … optimizing on-premises SQL Server data warehouses, focusing on stored procedures, indexing, partitioning, and load performance. A proven track record in designing and building data warehouses using Kimball methodologies, dimensional modeling, star schema design, and Data Vault techniques is essential. You should be well-versed in applying data architecture principles to create robust, scalable solutions Azure Cloud Proficiency: Deep 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 ❯

the design and implementation of the data architecture for our cutting-edge Azure Databricks platform focused on economic data. This platform is crucial for our Monetary Analysis, Forecasting, and Modelling efforts. The Data Architect will be responsible for defining the overall data strategy, data models, data governance framework, and data integration patterns. This role requires a deep understanding of … themes. Define the target data architecture and roadmap, considering scalability, performance, security, and cost-effectiveness. Stay abreast of industry trends and emerging technologies in data management and analytics. Data Modelling & Design: Design and implement logical and physical data models that support the analytical and modelling requirements of the platform. Define data dictionaries, data lineage, and metadata management processes. … e.g., APIs, databases, financial data providers). Work closely with data engineers to implement and optimise data pipelines within the Azure Databricks environment. Ensure data is readily available for modelling runtimes (Python, R, MATLAB). Data Governance & Quality: Establish and enforce data governance policies, standards, and procedures. Define data quality metrics and implement data quality monitoring processes. Ensure compliance More ❯

the mobile/telecoms industry would be a bonus! Key outputs for the role• Design, build, and maintain scalable and trustworthy data models in dbt, making use of Kimball Dimensional and One Big Table (OBT) methodologies.• Translate business requirements from stakeholders into robust, well-documented and tested dbt models.• Develop and own workflows within Google Cloud Platform environments, primarily … requirements and implement robust, well-documented and performantdbt models that serve as a single source of truth for business reporting.• Implement and champion data quality testing, documentation standards, and modelling best practices within dbt projects.• Troubleshoot and resolve any issues or errors in the data pipelines.• Stay updated with the latest cloud technologies and industry best practices to continuously … to see: • Expert level proficiency in SQL .• Deep, practical experience of building and architecting data models with dbt .• A strong understanding of data warehousing concepts and data modelling techniques (eg, Kimball, Dimensional Modelling, One Big Table).• Solid, hands-on experience within the Google Cloud Platform, especially with BigQuery.• Proven experience working directly with business 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 ❯

on your location) and home working (expectation is 2 days in the office) Permanent Full time, 37 hours per week Do you have prior experience of Enterprise Data Engineering, dimensional modelling? Do you have experience of working within an Agile environment or are keen to work in one? Do you like to always explore, learn, challenge yourself and … of new team members & coach other Data Engineers Actively contribute to drafting and updating our service policies, procedures, work instructions and guidance notes. As a BI Solution Architect/Dimensional Modeller, design robust, secure and supportable corporate data solutions to meet business requirements following dimensional modelling methodology, considering privacy by design and self-service capabilities by default. … be an Enterprise Data Engineer? Previous strong experience in data engineering ideally using Databricks, Azure Data Factory, Spark, Python, SQL, PowerBI Strong data engineering experience atleast 3-5 years Dimensional data modelling Experience in delivering end to end BI solution from requirements, design to delivery Experience of working within an Agile/Scrum environment Experience/understanding of More ❯

with a few in-person meetings in shared co-working spaces on an ad hoc basis. Role Description We are looking for an SQL Developer (Snowflake), specializing in data modelling, ETL processes, and cloud-based data solutions. This position requires expertise in Snowflake, Azure, Python and Power BI , with a strong focus on building semantic models and supporting analytics. … and translate them into scalable technical solutions. Ensure data quality, consistency, and performance across environments. Monitor and tune Snowflake performance, storage, and compute usage. Implement best practices in data modelling , schema design, and cloud architecture. Collaborate on CI/CD and automation initiatives for data deployments. Maintain technical documentation for processes, pipelines, models, and reports. Skills Required: Proven experience … code, especially within Snowflake stored procedures. Familiarity with modern cloud platforms for data integration, such as Azure Data Factory, Databricks, or similar tools. Experience in Power BI, including data modelling, DAX, and managing semantic models. Good understanding of data warehousing, dimensional modelling, and ELT best practices. Knowledge of version control and Agile development methodologies. Qualifications: Strong experience More ❯

solutions and languages (Spark, MPP, Python, Delta, Parquet). Experience with Azure DevOps & CICD processes, software development lifecycle including infrastructure as code (Terraform). Understand data warehousing concepts, including dimensional modelling, star schema, data aggregation, and best practices for designing efficient and scalable data models. Excellent documentation and diagramming skills. Technical Cloud Certification preferred e.g., Azure, Amazon Web More ❯

Catalog for data governance and cataloging. Familiarity with Terraform for infrastructure automation. Solid experience working with GitHub in a collaborative development environment. Deep understanding of data modeling concepts (e.g., dimensional modeling, star/snowflake schemas). Proven experience working with sales or transactional data. Ability to build and maintain clean, performant data layers for Power BI dashboards. More ❯

familiarity with version control systems. Understanding of enterprise data architecture patterns, including data lake, data warehouse, lakehouse, and cloud-native designs. Experience with Inmon, Data Vault 2.0, Kimball, and dimensional modelling. Knowledge of integration patterns, ETL/ELT processes, and tools (e.g., Apache Airflow, Azure Data Factory, Informatica, Talend) to orchestrate data workflows. Familiarity with DevOps/MLOps principles More ❯

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 ❯

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 ❯

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 ❯

experience Comprehensive Data Engineering background - proven track record in enterprise data solutions Experience with ETL processes and data transformation , preferably using Databricks Strong foundation in Data Warehousing architectures and dimensional modeling Familiarity with batch processing from relational database sources Communication & Collaboration Skills of the Data Engineer Outstanding stakeholder engagement abilities across technical and business audiences Strong relationship-building skills 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 ❯

one or more of these disciplines - data engineering/data modeling & data architecture/database design/data science & analytics • Expertise in SQL & Database design constructs, entity relationship modeling, dimensional modeling. • Experience in Relational and NoSQL databases (e.g., Oracle, Sybase, SQL Server, PostgreSQL, MongoDB) • Experienced in big data technologies like Hadoop & Snowflake • Prior experience of working with ETL tools More ❯

and supporting the data-driven solutions within our products and across the organisation. You should have in-depth knowledge of SQL databases (Microsoft or Postgres), and be familiar with dimensional modelling, star schema design and ETL processes. You will have the opportunity to be part of our strategic plan to incorporate machine learning and artificial intelligence into our … a data engineer (or similar) in an Agile environment ◦ Experience of SQL database systems and data warehousing, focusing on stored procedures, indexing, partitioning and load performance ◦ Experience of ETL, dimensional modelling and star schema solutions ◦ Technical expertise with data models, data mining, and segmentation techniques ◦ Have a strong understanding of data security and multi-tenancy ◦ Excellent communication skills More ❯

and supporting the data-driven solutions within our products and across the organisation. You should have in-depth knowledge of SQL databases (Microsoft or Postgres), and be familiar with dimensional modelling, star schema design and ETL processes. You will have the opportunity to be part of our strategic plan to incorporate machine learning and artificial intelligence into our … a data engineer (or similar) in an Agile environment ◦ Experience of SQL database systems and data warehousing, focusing on stored procedures, indexing, partitioning and load performance ◦ Experience of ETL, dimensional modelling and star schema solutions ◦ Technical expertise with data models, data mining, and segmentation techniques ◦ Have a strong understanding of data security and multi-tenancy ◦ Excellent communication skills 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 ❯

stewardship. Qualifications Programming: Python, SQL, Scala, Java. Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc. Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow). Data Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling. DevOps & Automation: Docker, Kubernetes, Terraform, CI/CD pipelines for data flows. Architectural Competencies Data Modelling: Designing … dimensional, relational, and hierarchical data models. Scalability & Performance: Building fault-tolerant, highly available data architectures. Security & Compliance: Enforcing role-based access control (RBAC), encryption, and auditing. Additional Information Discover some of the global benefits that empower our people to become the best version of themselves: Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral More ❯