3 of 3 Remote/Hybrid Azure Databricks Jobs in Central London

team through coaching and code reviews. Query and engineer large datasets (e.g., Python/R/SQL/PySpark) on modern platforms (e.g., Azure Databricks). Communicate pricing proposals and insights clearly and persuasively to stakeholders at all levels. Collaborate with Modelling, Optimisation, and Street Pricing teams … modelling techniques (e.g. GLMs and machine learning models). Proficiency in programming languages such as R, Python, PySpark, SAS, or SQL. Good knowledge of Azure Databricks and modern data technologies. Experience with WTW Radar software and optimisation tools. A quantitative degree in Mathematics, Statistics, Engineering, Physics, Computer Science ...

that can be used for invoice validation/cost reconciliation/supplier portfolio management. Design, develop, and maintain robust and scalable data pipelines using Azure Data Factory, Azure Databricks, and other relevant tools. Analysis: Automate routine analysis to drive reporting delivering rich business intelligence. Reporting: Support … related field; a master's degree is a plus. Proven experience in data engineering and analytics, with expertise in Power BI, dbt, Databricks, and Azure. Proficiency in SQL, Python, and data manipulation libraries and frameworks. Strong problem-solving skills and analytical thinking. Excellent communication skills with the ability ...

significant transformation across Data, AI and enterprise architecture. You'll take ownership of the enterprise data architecture strategy, leading the design of a modern Azure-based data platform while shaping how data products, governance and AI capabilities are embedded across the business. This is a leadership role with line … deliver a scalable, governed data ecosystem. Key Responsibilities Define and own the enterprise data architecture strategy and roadmap Lead the design of modern Azure lakehouse and data platform architectures Shape and embed enterprise data governance, modelling and architecture standards Drive the adoption of a data product operating model across ...