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The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step change in our ability to leverage data, knowledge, and prediction to find new medicines. We are 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 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 to unlock the value of our combined data assets and predictions in real-time
Director of Data Engineering is responsible for the design, delivery, support, and maintenance of industrialised automated end to end data services and pipelines. They apply standardised 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.
As a Director of Data Engineering, you are responsible for building and leading a scrum team of world-class data engineers focused on building automated, scalable, and sustainable pipelines to account for evolving scientific needs. You deeply influence the engineering direction of the Onyx platform, ensuring we built the best-in-class capabilities across data ingestion, streaming, transformation, knowledge, metadata, vectorized data pipelines and AI/GenAI integration. You support the head of Data Engineering in building a strong culture of accountability and ownership in you team, as well as instilling strong engineering practices (e.g., testing, code reviews, DevOps-forward ways of working). You work in close partnership with our Platforms teams to ensure we have the right tools and ways of working, and with our Bioinformatics teams to ensure the use of appropriate schemas, vocabularies, and ontologies. This role is for an engineer who combines hands-on expertise with strategic vision, operating oth as a senior builder, architect and technical thought leader
Key Responsibilities
Lead and mentor a team of data engineers in delivering data and knowledge products that advance GSK R&D
Architect and define the long-term data delivery and operational data engineering strategy in a complex and ambiguous data and knowledge ecosystem
Partner closely with other Data Engineering leads to drive standars for observability, scalability, performance optimization and operational excellence
Lead root-cause analysis and resolution of complex platform and pipeline issues and represent engineering in forums related to standards, compliance, technical strategy and cross R&D data initiatives
Collaborate with ML and GenAI teams to optimize and build data flows for fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) and champion data best practices for GenAI workfloads
Able to design innovative strategy beyond the current enterprise way of working to create a better environment for the end users, and able to construct a coordinated, stepwise plan to bring others along with the change curve
Standard bearer for proper ways of working and engineering discipline, including the QMS framework and CI/CD best practices and proactively spearhead improvement within their engineering area
Exemplar leaders in their field of technical knowledge, keen on bettering their understanding and acting as the knowledge holder for the organisation
Minimum Level of Job-Related Experience Required
20+ Years of Experience
Strong data engineering experience in industry
Software engineering experience
Demonstratable experience overcoming high volume, high compute challenges
Familiarity with orchestrating tooling
Cloud experience
Experience in automated testing and design
Experience with DevOps-forward ways of working
Job Related Experience sections above that are required for the job.
Deep knowledge and use of at least one common programming language: e.g., Python, Scala, Java
Deep experience with common big data tools (e.g., Spark, Kafka, Storm, …)
Cloud experience (e.g., AWS, Google Cloud, Azure, Kubernetes)
Application experience of CI/CD implementations using git and a common CI/CD stack (e.g., Jenkins, CircleCI, GitLab, Azure DevOps)
Experience with agile software development environments using tools like Jira and Confluence
Experience with Infrastructure as a Code and automation tools (i.e. Terraform)
Expertise in data modelling, database concepts and SQL
Nice to have familiarity with vector databases, embeddings, LLM data pipelines and RAG architecture
Skills
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Inclusion at GSK:
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Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.
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