Lead Data Architect

This 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 :