26 to 50 of 50 Permanent Dimensional Modelling Jobs

to the development of best practices and standards for data modeling and engineering within the team Support the data engineers during implementation Profil Strong experience in data modeling, including dimensional modeling, normalization/denormalization, and historization strategies Solid understanding of data engineering principles and ability to implement data models in production environments Hands-on mindset with the ability to More ❯

all data projects while engaging with senior stakeholders to deliver impactful solutions. Specifically, you can expect to be involved in the following: Designing and implementing both relational (3NF) and dimensional (star/snowflake) data models for large-scale financial systems and analytical platforms. Working hands-on with ETL design, metadata management, and data cataloguing , ensuring robust data lineage and … Visio , and handling semi-structured data formats (JSON, XML, Parquet). SKILLS AND EXPERIENCE The successful Data Modeller will have the following skills and experience: Proven experience in data modelling within consulting or financial services environments. Strong expertise in ERWin (or equivalent tools such as Sparx, RSA, Visio). Hands-on experience with relational and dimensional modelling More ❯

all data projects while engaging with senior stakeholders to deliver impactful solutions. Specifically, you can expect to be involved in the following: Designing and implementing both relational (3NF) and dimensional (star/snowflake) data models for large-scale financial systems and analytical platforms. Working hands-on with ETL design, metadata management, and data cataloguing , ensuring robust data lineage and … Visio , and handling semi-structured data formats (JSON, XML, Parquet). SKILLS AND EXPERIENCE The successful Data Modeller will have the following skills and experience: Proven experience in data modelling within consulting or financial services environments. Strong expertise in ERWin (or equivalent tools such as Sparx, RSA, Visio). Hands-on experience with relational and dimensional modelling More ❯

to a week. Travel and relocation are non-negotiable requirements. Must-Have Skills Python ETL/ELT Processes Web Crawling Data Cleaning SQL AWS (EC2, S3, Lambda, etc.) Elasticsearch Dimensional Modeling Data Pipeline Development English Communication (Advanced) Key Responsibilities: Design and deploy ETL/ELT processes using Python, SQL, and cloud tools. Perform web crawling, data cleaning, and annotation More ❯

business operations. Required and Preferred Qualifications: 5+ years of experience with Informatica PowerCenter, including hands-on development and performance tuning of ETL workflows. Strong understanding of data warehousing concepts, dimensional modeling, and ETL best practices. Experience with SQL and relational databases (e.g., Oracle, SQL Server) for data extraction and transformation. Proven ability to work with large datasets and optimize More ❯

Additional years of experience may be considered in lieu of a degree. Experience in transformation business requirements into optimal data model. Ideally experience working with customer analytics. Expertise in dimensional modeling (Star and Snowflake schemas) Experience with AWS Redshift and performance optimization Knowledge of AWS Glue, Redshift, Step Functions for data architecture Familiar with AWS DataZone for data lineage More ❯

will be responsible for automating testing, validation, and deployment to ensure data is reliable and trustworthy. Engineer the Data Warehouse: Design and build scalable data models (e.g., medallion architecture, dimensional models) to support analytical workloads, ensuring data is optimised for BI and reporting. Manage Data Infrastructure: Configure and optimize the underlying data infrastructure from a data engineering lens. This … CD pipelines for data solutions, specifically using Azure DevOps. Expert Programming Skills: Expert-level skills for data transformation and automation, especially in Python (PySpark) and advanced SQL. Data Warehousing & Modelling: Proven experience in data warehousing principles and designing data models (e.g., dimensional, medallion) to support analytics. Exceptional Communication: The ability to translate complex data concepts and trade-offs More ❯

ll bring: Experience in analytics, AI/data science, or data product environments - ideally within ad tech, media, or digital. Strong grasp of data warehousing concepts - data flows, ETL, dimensional modelling, and data quality. Solid SQL skills and the ability to interrogate complex data from diverse sources. Hands-on understanding of cloud-based data architectures A proven ability More ❯

Streams, Snowpark, Time Travel, Secure Data Sharing) to improve automation and accessibility. Collaboration: Work closely with analysts and stakeholders to deliver data products and troubleshoot issues. Analytics Enablement: Implement dimensional models to provide clean, reusable datasets for reporting and advanced analytics. Monitoring & Reliability: Maintain monitoring, alerting, and cost-management processes for Snowflake and pipelines. Continuous Improvement: Contribute to shared … transformations and pipeline automation. Practical experience with Snowflake features and RBAC management. Familiarity with ingestion tools (Airbyte, Fivetran, Hevo) and cloud services (AWS preferred). Solid understanding of data modelling, governance principles, and BI enablement (Power BI). Knowledge of CI/CD and version-controlled development practices in git. Desirable: Experience with enterprise systems (CRM, BSS/OSS More ❯

the right time. Essentially, to ensure you succeed in this role you're going to need Deep, hands-on experience designing and building data warehouses with strong command of dimensional modeling (e.g., Kimball methodology) Expertise in Google Cloud Platform, especially BigQuery architecture, optimization, and cost management Advanced SQL skills and production-level experience using dbt (or similar tools) to More ❯

analytics technologies-for example, cloud platforms (e.g., Azure Synapse, AWS Redshift, GCP BigQuery), ETL frameworks, data modeling tools, and data governance platforms. Hands-on experience with both relational and dimensional modeling techniques, modern data lakehouse design, and scalable pipeline architecture. Exposure to conceptual and logical data modelling practices for enterprise-wide data architecture. A solid understanding of data More ❯

Data Delivery Team in designing and building scalable, future-proof data assets within the Microsoft Azure ecosystem. This role involves technical consulting, hands-on development, and leadership in data modelling, orchestration, and semantic layer design. Key Responsibilities: Provide technical consulting to the Data Engineering Manager during the design phase. Collaborate with a small team of Business Data Engineers to … build new data assets. Lead the design and development of dimensional data models and Power BI semantic models. Replace legacy SAP Business Objects universes with modern Azure-based solutions. Utilize Azure Data Factory (ADF), stored procedures, and Azure Synapse for data processing. Guide the team on best practices, architecture, and documentation standards. Engage with stakeholders to ensure solutions are … Experience: 10+ years of experience in data engineering, BI, or data architecture roles. Strong expertise in Azure Synapse, ADF, SQL, and Power BI. Proven experience in designing and implementing dimensional models and semantic layers. Familiarity with metadata management tools (e.g., Collibra) and model curation tools (e.g., Tabular Editor). Excellent communication and stakeholder management skills. Experience working in agile More ❯

Business Intelligence Engineer 12 Months Hybrid - London Inside IR35 Up to £500 a day Key Skills: Data modelling, data warehousing, Dashboarding Technical: AWS, SQL Python Key Responsibilities: - Build End to End dashboarding solutions to optimize EU CF Operations using AWS - Data source exploration, data warehousing expansion, horizontal datasets for downstream consumption - Work with customers to build Dashboards with the … 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 ❯

central Data Platform, working closely with the Data Management Team. Analysis of normalised transactional data and analytic data sources. Analysis of semi-structured and file-based data extracts. Data modelling to transform operational data into analytic/reporting structures such as Kimball-style multi-dimensional models. 💡Strong SQL, Sigma, PowerBI, Matilion, DBT, Python Essential Skills for the Lead … Data Analyst: Proven Data Analyst experience of at least 5 years, within a Financial Services environment, with particular emphasis on Risk or cross asset derivatives areas. Data modelling, cleansing and enrichment, with experience in conceptual, logical and physical data modelling and data cleansing and standardisation. Familiarity with Data warehousing and analytical data structures. Data quality assurance, validation and More ❯

central Data Platform, working closely with the Data Management Team. Analysis of normalised transactional data and analytic data sources. Analysis of semi-structured and file-based data extracts. Data modelling to transform operational data into analytic/reporting structures such as Kimball-style multi-dimensional models. 💡Strong SQL, Sigma, PowerBI, Matilion, DBT, Python Essential Skills for the Lead … Data Analyst: Proven Data Analyst experience of at least 5 years, within a Financial Services environment, with particular emphasis on Risk or cross asset derivatives areas. Data modelling, cleansing and enrichment, with experience in conceptual, logical and physical data modelling and data cleansing and standardisation. Familiarity with Data warehousing and analytical data structures. Data quality assurance, validation and More ❯

feedback efficiently in an iterative manner Develop and abide by standard methodologies for scalable and repeatable insights. Translate existing spreadsheets/mockups and business problems into sophisticated Anaplan multi-dimensional models Modify existing models as part of a connected solution, optimization, or to incorporate new functionality Implement standard processes and documentation for Anaplan models Lead data integration and migration More ❯

Key Responsibilities: 1. Data Modeling & Curated Layer Design Design logical, conceptual, and physical data models for EDPs curated layer in BigQuery. Develop fact and dimension tables, ensuring adherence to dimensional modeling best practices (Kimball methodology Optimize data models for performance, scalability, and query efficiency in a cloud-native environment. Work closely with data engineers to translate models into efficient … e.g., Looker, Tableau, Power BI, AI/ML models, APIs Required Qualifications: 5+ years of experience in data modeling and architecture in cloud data platforms (BigQuery preferred Expertise in dimensional modeling (Kimball), data vault, and normalization/denormalization techniques. Strong SQL skills, with hands-on experience in BigQuery performance tuning (partitioning, clustering, query optimization Understanding of retail data models More ❯

data systems You Will Demonstrate Deep knowledge of the Azure data stack (Azure SQL Server, CosmosDB, Azure Data Factory, Purview, Synapse, Event Hub, Azure Databricks/Fabric) Extensive data modelling experience: both normalised relational models and de-normalised Star Schema/dimensional models Excellent relational database design skills with expertise in diagnosing and optimising performance across SQL Server More ❯

most relevant data from Snowflake to support business questions and performance tracking. o Conduct exploratory data analysis to uncover trends, anomalies, and opportunities for improvement in logistics operations. Data Modelling and Metric Logic o Design and maintain scalable data models that reflect logistics processes and support cross-functional reporting. o Define and implement logic for KPI generation and performance … Proficiency in designing scalable and efficient data models using Snowflake. Experience with SQL for querying, transforming, and preparing data for analysis and visualization. Understanding of data warehousing principles and dimensional modeling. • Data Integration and ETL: Knowledge of ETL processes, data extraction, and transformation, along with experience in SQL and data connectors. • Data Analysis and Visualization: Skills in visualizing data More ❯

helping enterprise clients structure, govern, and leverage data effectively. The Role As a Senior Data Modeller, you will act as a hands-on lead across client projects, setting data modelling standards and ensuring delivery across multiple stakeholders. You will design frameworks, define best practice for data structures, and drive consistency across systems while remaining highly involved in technical delivery. … Key Responsibilities Lead on data modelling design and implementation across client programmes Create relational and dimensional models for enterprise data warehouses and analytics platforms Define metadata standards, data catalogues, and lineage documentation Collaborate with architects, engineers, and business stakeholders to ensure data models meet business needs Support data migration, governance, and transformation initiatives Your Skills and Experience 5+ … years of experience in data modelling or architecture, ideally within financial services or consulting Strong knowledge of relational and dimensional design (3NF, star, snowflake) Proficient in ERWin, Sparx, or similar tools Experience working with semi-structured data (JSON, XML, Parquet) Excellent communication and client-facing skills More ❯

across the organisation. Key Responsibilities: Design and maintain scalable data platforms using cloud-native technologies such as Databricks and AWS across development, staging, and production environments Build and govern dimensional data models and semantic layers to power consistent and trusted analytics Integrate data from diverse sources including cloud warehouses, APIs, and operational systems Define semantic layers using dbt and … to ensure performance and cost efficiency Collaborate with cross-functional teams on architecture decisions, technical designs, and data governance standards You Will Have: Proven hands-on expertise in data modelling with a strong track record of designing and implementing complex dimensional models and enterprise-wide canonical data models The ability to translate complex business processes into scalable and More ❯

across the organisation. Key Responsibilities: Design and maintain scalable data platforms using cloud-native technologies such as Databricks and AWS across development, staging, and production environments Build and govern dimensional data models and semantic layers to power consistent and trusted analytics Integrate data from diverse sources including cloud warehouses, APIs, and operational systems Define semantic layers using dbt and … to ensure performance and cost efficiency Collaborate with cross-functional teams on architecture decisions, technical designs, and data governance standards You Will Have: Proven hands-on expertise in data modelling with a strong track record of designing and implementing complex dimensional models and enterprise-wide canonical data models The ability to translate complex business processes into scalable and More ❯

helping enterprise clients structure, govern, and leverage data effectively. The Role As a Senior Data Modeller, you will act as a hands-on lead across client projects, setting data modelling standards and ensuring delivery across multiple stakeholders. You will design frameworks, define best practice for data structures, and drive consistency across systems while remaining highly involved in technical delivery. … Key Responsibilities Lead on data modelling design and implementation across client programmes Create relational and dimensional models for enterprise data warehouses and analytics platforms Define metadata standards, data catalogues, and lineage documentation Collaborate with architects, engineers, and business stakeholders to ensure data models meet business needs Support data migration, governance, and transformation initiatives Your Skills and Experience 5+ … years of experience in data modelling or architecture, ideally within financial services or consulting Strong knowledge of relational and dimensional design (3NF, star, snowflake) Proficient in ERWin, Sparx, or similar tools Experience working with semi-structured data (JSON, XML, Parquet) Excellent communication and client-facing skill More ❯

helping enterprise clients structure, govern, and leverage data effectively. The Role As a Senior Data Modeller, you will act as a hands-on lead across client projects, setting data modelling standards and ensuring delivery across multiple stakeholders. You will design frameworks, define best practice for data structures, and drive consistency across systems while remaining highly involved in technical delivery. … Key Responsibilities Lead on data modelling design and implementation across client programmes Create relational and dimensional models for enterprise data warehouses and analytics platforms Define metadata standards, data catalogues, and lineage documentation Collaborate with architects, engineers, and business stakeholders to ensure data models meet business needs Support data migration, governance, and transformation initiatives Your Skills and Experience 5+ … years of experience in data modelling or architecture, ideally within financial services or consulting Strong knowledge of relational and dimensional design (3NF, star, snowflake) Proficient in ERWin, Sparx, or similar tools Experience working with semi-structured data (JSON, XML, Parquet) Excellent communication and client-facing skill More ❯

directed. Provide a list of the day to day tasks to be performed by the Selected Candidate: Perform Data profiling on the source systems Design and review star schema dimensional model to support data warehouse and data marts Perform Source to Target Mapping between source system database and data warehouse target database Develop analytics and reports using Tableau and … other similar ETL tool 2. 36 months experience in analytics and operational reporting using Tableau and SQL Server Reporting Services (SSRS 3. 36 months experience in Star Schema/Dimensional Modeling to support data warehouse environments as well as OLTP environments. 4. 48 months experience developing and tuning complex SQL and PL/SQL against Oracle (11g or newer More ❯