10 of 10 Contract Dimensional Modelling Jobs

Server, SSIS, SSAS, SSRS) Hands-on experience building and maintaining data pipelines and integrations (ETL/ELT) Solid understanding of data warehousing concepts, dimensional modelling, and data normalisation Experience with data manipulation languages such as T-SQL and DAX Experience working in an Agile environment (ideally Kanban) Strong ...

strategies. Experience integrating data via APIs and services. Clear communication skills and experience working in Agile delivery teams. Nice to Have: Data warehousing and dimensional modelling (e.g. dbt). Basic Power BI knowledge. Relevant Microsoft or Azure certifications. Reasonable Adjustments: Respect and equality are core values to us. ...

Server, SSIS, SSAS, SSRS) Hands-on experience building and maintaining data pipelines and integrations (ETL/ELT) Solid understanding of data warehousing concepts, dimensional modelling, and data normalisation Experience with data manipulation languages such as T-SQL and DAX Experience working in an Agile environment (ideally Kanban) Strong ...

hands-on experience with SSIS and SQL Server. Proven ability to deliver reliable, scalable data warehouse solutions. Strong understanding of data modeling principles, including dimensional modeling and slowly changing dimensions. Experience in ETL/ELT design and development. Familiarity with data quality and profiling techniques. Background in building ...

. Technical Expertise: Strong expertise in Microsoft Data Platform technologies, including: SQL Server SSIS SSAS SSRS Solid understanding of data warehousing concepts, data normalisation, dimensional modelling, and associated best practices. Hands-on experience with data pipelines and integrations (ETL/ELT). Proficiency in data manipulation languages such ...

. Technical Expertise: Strong expertise in Microsoft Data Platform technologies, including: SQL Server SSIS SSAS SSRS Solid understanding of data warehousing concepts, data normalisation, dimensional modelling, and associated best practices. Hands-on experience with data pipelines and integrations (ETL/ELT). Proficiency in data manipulation languages such ...

closely with data engineers, analysts, and architects to deliver high-quality, scalable data pipelines and models. Strong expertise in Snowflake, ETL/ELT, data modelling, and data warehousing is essential. Responsibilities Snowflake Development: Build and optimise Snowflake objects (databases, schemas, tables, views, tasks, streams, resource monitors). ETL/… Pipelines: Develop and maintain robust data pipelines using tools like dbt, Airflow, Azure Data Factory, or similar. Data Modelling: Implement dimensional models (star/snowflake schemas), handle SCDs, and design efficient structures for analytics. Performance Tuning: Optimise queries, manage clustering, caching, and warehouse sizing for cost and speed. ...

experience with complex data transformations Experience with cloud platform - Azure Familiarity with ETL/ELT tools Strong understanding of data warehousing concepts and dimensional modelling Responsibilities Design, develop, and maintain data pipelines and data models in Snowflake Implement ELT/ETL processes using Snowflake and associated tools Optimise ...

Blocks Source system classification and data contracts Ingestion and landing architecture Standardisation validation and data quality layers Master and reference data integration Analytical and dimensional modelling approaches Semantic layer and BI consumption patterns Metadata lineage observability and monitoring Architecture Leadership Act as architectural authority and design reviewer Produce ...

architecture, and building data models. Proficiency in data profiling and source system analysis. Experience in developing data standards for specific components, including relational and dimensional models, as well as adhering to FAIR principles and industry best practices. Knowledge of modelling frameworks and standards, such as UML and TOGAF … including PaaS solutions (SQL Server, Synapse) and SaaS applications (Fabric), as well as Databricks. Familiarity with various data patterns and data types, including relational, dimensional, structured and unstructured data, medallion architecture patterns, API patterns, security, and integrations. Knowledge of data management and governance processes and practices, following the Data ...