26 to 50 of 125 Permanent Dimensional Modelling Jobs

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 ❯

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 ❯

analysis techniques and data usage and building solutions to enable. Experience Strong technical background and proven ability in data collection, transformation and integration, evidencing understanding of data warehousing and dimensional modelling principles with good understanding of data profiling or analysis. Data modelling. You understand the concepts and principles of data modelling and can produce relevant data models. More ❯

Snowflake, Power BI, Python, and SQL. Your work will enable self-service analytics and support data governance across the business. Key Responsibilities: Develop robust ETL/ELT pipelines and dimensional models for BI tools Define and implement data quality, ownership, and security standards Empower business teams with intuitive, self-serve data models Own data products end-to-end, from … design to continuous improvement Promote innovation and best practices in data engineering About You: Strong experience with SQL, Python, and BI tools (e.g., Power BI) Solid understanding of dimensional modelling and data architecture Experience working in governed, decentralised data environments Excellent communication and stakeholder engagement skills Analytical mindset with a focus on delivering business value If you are 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 ❯

DBA) Azure Databricks Azure Data Factory Microsoft Fabric Power BI, DAX Azure Data Lake Supporting: Azure ML Azure AI Services Azure Infrastructure Python, PySpark Microsoft Purview Principles: Relational and Dimensional Modelling Data Warehouse Theory Data platform Architecture models such as Lakehouse Data Science Master Data Management Data Governance Additional Information We don’t believe hiring is a tick More ❯

Private Medical Health Pension Scheme And more... Candidate requirements include experience in: Extensive experience with solutions involving Databricks, Azure Data Factory, Synapse Excellent understanding of Microsoft SQL Server, Data Modelling, Data Marts, Dimensional Modelling Understanding of SQL/database management Strong understanding of the wider Azure stack (ADF, Synapse, ADLS) and Data Modelling tools (ERwin, ER More ❯

Bachelor’s or master’s degree in a relevant field 5+ years of proven experience as a Data Engineer Strong knowledge of SQL and relational databases Experience with data modelling, data warehouses, data lakes, and ETL Familiarity with cloud-based BI solutions Experience with dimensional modelling Solid analytical and communication skills Fluent in Dutch (written and spoken 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 ❯

Partners, we are expanding our Data Services team, investing in a large-scale modernisation programme to drive innovation and insights. We’re building a new team to enhance data modelling, reporting, AI initiatives, and cloud data platforms like Snowflake. As part of our transformation, we’re growing our analytics capability to help develop the understanding of commercial performance and … 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. As a Data Engineer, your responsibilities will include: Design, develop, and implement data warehouse solutions using … Partners, we are expanding our Data Services team, investing in a large-scale modernisation programme to drive innovation and insights. We’re building a new team to enhance data modelling, reporting, AI initiatives, and cloud data platforms like Snowflake. As part of our transformation, we’re growing our analytics capability to help develop the understanding of commercial performance and More ❯

Business Intelligence Engineer Hybrid – London Up to £450 a day Inside IR35 6 Months Key Skills: Business Intelligence (Data modelling, data warehousing, Dashboarding) SQL & Python AWS (S3, Lambda, Glue, Redshift) The Senior Business Intelligence Engineer occupies a unique role at the intersection of technology, marketing, finance, statistics, data mining, and social science. We provide the key insight into customer … using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills: - Strong analytical and problem-solving abilities - Excellent understanding of dimensional modeling and star schema design (Facts, dimensions, scd type 2) - Experience with agile development methodologies - Strong communication skills and ability to work with cross-functional teams - Background in data More ❯

Business Intelligence Engineer Hybrid – London Up to £450 a day Inside IR35 6 Months Key Skills: Business Intelligence (Data modelling, data warehousing, Dashboarding) SQL & Python AWS (S3, Lambda, Glue, Redshift) The Senior Business Intelligence Engineer occupies a unique role at the intersection of technology, marketing, finance, statistics, data mining, and social science. We provide the key insight into customer … using AWS CDK - Proficiency in ETL/ELT processes and best practices - Experience with data visualization tools (Quicksight) Required Skills: - Strong analytical and problem-solving abilities - Excellent understanding of dimensional modeling and star schema design (Facts, dimensions, scd type 2) - Experience with agile development methodologies - Strong communication skills and ability to work with cross-functional teams - Background in data More ❯

in SQL and Python for data transformation and workflow automation Experience with AWS data tools (e.g. Redshift, Glue, Lambda, S3 ) and infrastructure tools such as Terraform Understanding of data modelling concepts (e.g. dimensional models, star/snowflake schemas) Knowledge of data quality, access controls , and compliance frameworks Nice to Have Experience with orchestration or pipeline frameworks like Airflow 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 ❯

solutions to both technical and non-technical audiences, tailoring communication style based on the audience. Data Modeling and Warehousing: •Design and implement data models optimized for analytical workloads, using dimensional modeling techniques (e.g., star schema, snowflake schema). •Participate in the design, implementation, and maintenance of data warehouses ensuring data integrity, performance, and scalability. BASIC QUALIFICATIONS •Educational Background: Bachelor … optimization. •Programming/Statistical Analysis Skills: Working knowledge of R or Python for analytics, data manipulation, and algorithm development. •Data Warehousing Knowledge: In-depth knowledge of data warehousing principles, dimensional modeling techniques (e.g., star schema, snowflake schema), and data quality management. •Communication and Collaboration Abilities: Excellent verbal and written communication skills, with the ability to effectively communicate technical concepts More ❯

using Excel dashboards Enable teams with self-service analytics and standardized templates Extract, transform, and load data from EDW platforms (e.g., Azure Synapse, SQL Server, Snowflake) Design and validate dimensional models (star/snowflake schemas) Work with data architects and engineers to align EDW data with reporting needs Maintain data consistency, integrity, and governance across systems Develop and manage 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 ❯

CDK. Proficiency in ETL/ELT processes and best practices. Experience with data visualization tools such as Quicksight. Required Skills: Strong analytical and problem-solving abilities. Excellent understanding of dimensional modeling and star schema design (facts, dimensions, SCD type 2). Experience with agile development methodologies. Strong communication skills and ability to collaborate with cross-functional teams. Background in More ❯