The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.

Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:​

• Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”​
• Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent​
• Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time​

The Onyx Data Architecture team sits within the Data Engineering team, which is responsible for the design, delivery, support, and maintenance of industrialized automated end to end data services and pipelines. They apply standardized data models and mapping to ensure data is accessible for end users in end-to-end user tools through use of APIs. They define and embed best practices and ensure compliance with Quality Management practices and alignment to automated data governance. They also acquire and process internal and external, structure and unstructured data in line with Product requirements.

The Senior Data Architect should bring deep knowledge of designing and leading Big Data Architecture in a highly complex, heterogeneous environment. R&D is a highly complex and regulated environment and therefore you need to have deep knowledge of the applicable business area to be successful in this role. You must demonstrate excellent data architecture skills to define principles, standards and patterns for building a Data Mesh/Data Fabric architecture using our Target Data Platforms.

You will be responsible for…

• Collaborating with Data Platform Teams, Data Engineers, and Architects to build, maintain and govern data architecture principles, standards, and guidelines
• Producing conceptual, logical, and physical data models to build fit for purpose data products
• Define various data pipeline architecture patterns aligned with DataMesh/Data Fabric architecture on Target platforms
• Partner and work with Data Engineers, Data Testers, Architects, AI/ML Specialists to drive the Data and Analytics strategy
• Building data architecture spanning different business areas and drawing links between problems to build common solutions
• Collaborating with different business areas and stakeholders to ensure consistent implementation of Data Architecture principles/standards across Target platforms
• Designing data architecture aligned with Enterprise-wide standards and principles to promote interoperability

• Adopting a security-first design that embeds robust authentication, hardened infrastructure and resilient connectivity across the Data and data platform environments.

• Providing leadership to team members to help others get the job done right
• Supporting engineering teams in the adoption and creation of data Mesh best practices.
• Maintaining best practices for data architecture on our Confluence site. 
• Pro-actively engaging in experimentation and innovation to drive relentless improvement 
• Providing leadership, Subject Matter, and GSK expertise to architecture and engineering teams composed of GSK FTEs, strategic partners, and software vendors.

Why you? 

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• Bachelor’s degree in computer science, engineering, Data Science or similar discipline ​
• 7+ years of experience in data architecture, data engineering, or related fields in pharma, healthcare, or life sciences R&D.
• 5+ years’ experience of defining architecture standards, patterns on Big Data platforms
• 5+ years’ experience with data warehouse, data lake, and enterprise big data platforms
• 5+ years’ experience with enterprise cloud data architecture (preferably Azure or GCP) and delivering solutions at scale 
• 5+ years of