26 to 50 of 57 Dimensional Modelling Jobs in London

skills in building dashboards and using visualisation tools such as Tableau (beneficial), Power BI or Looker. Experience in database design and architecture principles, e.g. dimensional modelling and strong SQL ability Some understanding or interest in programming languages such as Python. Exposure to working with CRM/ERP systems. More ❯

Data Platform technologies. - On prem and Azure knowledge - A good understating of all things data - data integration, warehousing, advanced analytics, etc - Strong knowledge of dimensional modelling techniques - Familiarity of data engineering tools and automation practices (CI/CD pipelines, DevOps etc) This is an excellent role for a More ❯

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 … 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 … 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 More ❯

Collaborating with analytics and data scientists to understand their needs and build models that drive insights and decision making Champion best practices for data modelling, transformation, and governance, in your immediate time and across the business Consult on our evolving data platform, advising on the tooling, infrastructure and practices … efficient and well structured queries Hands on experience with DBT, building and maintaining modular, scalable data models that follow best practices Strong understanding of dimensional modelling Familiarity with AWS data services (S3, Athena, Glue) Experience with Airflow for scheduling and orchestrating workflows Experience working with data lakes or More ❯

concepts. Knowledge of agile methodologies and use of the Rally application. Working knowledge of creation of Entity Relationship Diagrams and Data flow diagrams and Dimensional modelling. Working knowledge of Exploratory data analysis techniques. Working knowledge of Quality Center. Working knowledge: understands basic principles and terminology in order to understand More ❯

2+ years of experience in PySpark. Knowledge of GCP Kubernetes would be an advantage. Knowledge of data warehousing concepts with a good understanding of dimensional models. Experience in implementing a metadata framework for data ingestion, data quality, and ETL. Good communication skills and ability to manage IT stakeholders. More ❯

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 Document data lineage and recommend improvements for data ownership and stewardship. Qualifications Programming: Python, SQL More ❯

of translating sophisticated business challenges into effective solution designs for clients. Your Impact Convert existing solutions, spreadsheets, and business problems into advanced Anaplan multi-dimensional models. Adjust existing models to optimize or incorporate new functionality as part of a connected solution. Act as the architectural SME for large-scale More ❯

designs. Ensure alignment of low-level designs with application architecture, high-level designs, and AA Standards, Frameworks, and Policies. Analyse data sets to identify modelling logic and key attributes required for low-level design, and create and maintain appropriate documentation. Develop and update Physical Data Models (PDMS) and participate … with data warehouse and business intelligence, including delivering low-level ETL design and physical data models. Proficient in Data Warehousing Design Methodologies (e.g., Kimball dimensional models) and Data Modelling tools (e.g., ER Studio). Strong Data Analysis skills and hands-on experience with SQL/Python for data More ❯

opportunities to travel if required Required Skills and Experience Educated to degree level Demonstrated analytical and troubleshooting skills A background in financial/multi-dimensional modelling within an FP&A or Analyst team or with a Consulting background desirable High proficiency to understand and interrogate complex business data More ❯

opportunities to travel if required Required Skills and Experience Educated to degree level Demonstrated analytical and troubleshooting skills A background in financial/multi-dimensional modelling within an FP&A or Analyst team or with a Consulting background desirable High proficiency to understand and interrogate complex business data More ❯

or equivalent. SQL Programming. C# Software development. Knowledge and Skills C# Programming to high level of proficiency. Software analysis and design. SQL query language. Dimensional modelling Data warehouse design concepts, (Inmon or Kimball) The Client is a Bank based in the City of London. This is a More ❯

or equivalent. SQL Programming. C# Software development. Knowledge and Skills C# Programming to high level of proficiency. Software analysis and design. SQL query language. Dimensional modelling Data warehouse design concepts, (Inmon or Kimball) This is a Full-Time Contract initially for 6 months - but likely to become permanent. More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

is a plus Strong knowledge of modern data stack tools, including Airbyte, dbt (MUST HAVE), Snowflake, and cloud platforms like AWS. Familiarity with data modelling concepts and warehousing best practices, including dimensional modelling. Experience delivering data solutions using software engineering principles, including version control (GitHub). A proactive More ❯

At least 1 year of experience in implementing a data model for an enterprise analytical platform. 4+ years of experience in developing ER and Dimensional models. Experience in the Investment domain is a must, with knowledge of Fund, Holdings, Cashflow, etc. Experience in building conceptual, logical, and physical models. More ❯

with customer teams to transform and optimize business processes through the Anaplan Platform Translating existing solutions, spreadsheets, and business problems into sophisticated Anaplan multi-dimensional models Supporting scoping, estimations, and customer presentations as part of a Solution Sales process Assisting with knowledge management, mentoring, and enablement across the Professional More ❯

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. Essential Skills for the 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 More ❯

technical components (e.g. ETL, Reporting, and Data Modeling), infrastructure (e.g. hardware and software) and their integration. The ideal candidate will have extensive experience in dimensional modeling, excellent problem-solving ability dealing with huge volumes of data and a short learning curve. Excellent written and verbal communication skills are required … large-scale, complex datasets using traditional or map reduce batch mechanism. Strong data modeling skills with solid knowledge of various industry standards such as dimensional modeling, star schemas, etc. Extremely proficient in writing performant SQL working with large data volumes. Experience designing and operating very large Data Warehouses. Experience More ❯