Working within the group's core Data & Analytics function, this position will hold the following responsibilities:Delivering technical functionality developed against the Global Azure Data Platform.Creating and maintain optimal data pipeline architecture in Azure.Drive best practice development and design, working with the wider team to implement solutions that deliver quality, usable insights to multiple business users and functions.Assembling large, complex data sets that meet functional / non-functional business requirements.Identifying, designing, and implementing internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.Building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure 'big data' technologies.Working with stakeholders including the Executive, Product and Data teams to assist with data-related technical issues and support their data infrastructure needs.Keeping internal data separated and secure across national boundaries through well architected sensitive data patterns and later enhancements to include regions in Azure.Creating data tools for analytics and data scientist team members that assist them in building and optimising our product into an innovative industry leader.Working with data and analytics experts to strive for greater functionality in data systems.Key skills and experience required:Extensive commercial experience as a Senior data engineer experience leading Digital Data transformation programmes, including experience in Azure cloud development.Expert experience with Azure Data Factory, Azure Databricks specificallyExperience with other Microsoft cloud services including Azure Logic Apps, Azure Functions, Azure Storage, Azure Data Lake, Synapse.Involvement in or delivery of a successful multi regional digital data initiative.Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.Experience building and optimising 'big data' data pipelines, architectures and data sets.Build processes supporting data transformation, data structures, metadata, dependency, and workload management.A successful history of manipulating, processing and extracting value from large, disconnected datasets.Familiarity with data modelling architectures (Kimball/Inmon) and its implementationFamiliarity with metadata driven (contract) frameworks on cloudExperience with version and source control (Git) and Azure DevOpsExperience in APIs and API Management