Data Engineer

As a Data Engineer at GSK, you will shape how product and process data is modeled, connected and reused across digital products and manufacturing systems. You’ll work with R&D, CMC and commercial data to enable scalable data access and analytics, using ontologies, knowledge graphs and AI where appropriate. You will design data pipelines and integrations within enterprise guardrails, ensuring security, quality and traceability. This role offers the chance to impact data-driven decisions across R&D to commercial platforms and to mentor peers in pragmatic engineering patterns. You will join a cross-functional team driving responsible AI and data standards at scale.

• Set up and maintain CI/CD pipelines and integration flows for PDLM data between systems
• Keep pipeline and mapping code under version control with automated checks and peer reviews
• Leverage approved AI tools while adhering to Responsible AI, privacy and security requirements
• Design data and integration services within enterprise architecture guardrails and document decisions
• Define environment promotion flows for data and integration services across R&D, CMC and commercial use
• Support end-to-end releases and integrations with automated deployments and change-control
• Collaborate with ontology/knowledge-graph teams to implement data structures and mappings
• Work with AI/analytics teams to provision data pipelines and access patterns for AI proofs of concept
• Design and support integration patterns between PDLM and MES/LES/LIMS/ERP and other platforms
• Apply AI-assisted development with validation for accuracy, security and data integrity
• Monitor data pipelines and remediation of recurring issues
• Document data flows, contracts, deployment patterns and runbooks
• Coach engineers and analysts to reuse patterns and templates
• Define and maintain data and integration engineering standards and reusable models
• Drive continuous improvement in reliability, observability, performance and security

• Bachelor's degree in Computer Science, Information Technology, Software Engineering or related discipline
• Significant experience in data engineering, integration engineering, DevOps or similar roles in complex environments
• Experience designing data and integration solutions spanning R&D, CMC and/or manufacturing domains (PDLM or similar)
• Experience with ontologies, vocabularies or knowledge-graph technologies
• Experience enabling AI/ML or advanced analytics through well-designed data sets
• Experience with AI-assisted development and Responsible AI, data privacy and cyber security controls
• Experience integrating manufacturing, lab or quality systems (MES, LES/LIMS, ERP, regulatory/CMC)
• Experience deploying and operating data/integration services with DevOps/platform teams

• Strong collaboration across global teams
• Analytical and problem-solving mindset
• Clear technical writing and documentation discipline
• CI/CD
• Cloud-based services
• API Management