At GSK we are building a best-in-class data and prediction powered team that is ambitious for patients.Scientific Digital and Techs goal is to power the discovery, development and supply of medicines and vaccines to patients. This means new tools to discover new medicines and vaccines, predictive capability for pre-clinical research, accelerated CMC and supply chain and an improved day-to-day laboratory experience for our scientists. Our Digital & Tech solutions will automate workflows and speed up decisions; freeing hands and releasing minds to focus on science.As R&D enters a new era of data driven science, we are building a data engineering capability to ensure we have high quality data captured with context and aligned data models, so that the data is useable and reusable for a variety of use cases.GSK R&D and Digital and Techs collective goal is to deliver business impact, including the acceleration of the discovery and development of medicines and vaccines to patients. The R&D Digital and Tech remit has expanded over the past 2 years, and to position GSK for the future, The change will strengthen R&D Tech, to provide more strategic impact, focus, accountability, and improved decision making in the use of Digital, Data and Analytics (DDA) to strengthen the pipeline.Job PurposeThis role contributes to the construction of the development data fabric and data strategy. This role will interact with architects, engineers, data modelers, product owners as well as other team members in Clinical Solutions and R&D. This role will actively participate in creating technical solutions, designs, implementations & participate in the relentless improvement of R&D Tech systems in alignment with agile and DevOps principles.The Data Engineer demonstrates both depth and breadth across key data engineering competencies e.g. Software Development, Testing, DevOps, Data Science/Analytics, and cloud. Can collaborate with experts from other subject domains. Primary responsibilities include using Azure cloud services and GSK data platform tools to ingest, egress, and transform data from multiple sources.In addition, the role will demonstrate core engineering knowledge/experience of industry technologies, practices, and frameworks such as data fabric and scaling data platforms, containerization, cloud-based platforms, data analytics, machine learning, and data streaming. Examples of technologies include Java/C#/Python, Denodo, GIT, Azure Devops, Data Bricks, Presto, Spark, Azure Data Factory, ADLS V2, Kafka, Selenium, JUnit/NUnit, SAFe, Kanban, Docker, AI/ML, Azure/GCP Cloud Architecture including networking principles and scaling applications.The Data Engineer, Clinical Solutions role is a senior technical role and will provide you the opportunity to lead key activities to progress your career. These responsibilities include the following:
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