Data Engineer

The Data Engineer provides technical leadership for how product and process information is structured, connected and reused across digital products and manufacturing systems, with a particular focus on the digital product profile.

In this role you will:

• Set up and maintain CI/CD pipelines and integration flows that move digital product profile and related data between PDLM and other systems.
• Ensure pipeline, integration and mapping code is kept under version control, automatically tested and peer-reviewed before release.
• Use approved AI tools to improve productivity and team working.
• Own the design of data and integration services within enterprise architecture guardrails.
• Define environment promotion flows for data and integration services.
• Support releases and integrations end-to-end.
• Work with R&D and central ontology teams to implement and operate data and metadata structures.
• Collaborate with AI and analytics teams to provision data pipelines and integrations.
• Design and support integration patterns between PDLM and key downstream systems.
• Make practical use of AI-assisted development and validate outputs.
• Monitor and troubleshoot data pipelines and related services.
• Document data flows, integration contracts and deployment patterns.
• Coach engineers and analysts working on digital product profile and data integration work.
• Define and maintain data and integration engineering standards.
• Drive continuous improvement in reliability, observability, performance and security.

Basic Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering or a related discipline.
• Significant experience in data engineering, integration engineering, DevOps or similar roles.
• Experience designing and delivering data and integration solutions that span R&D, CMC and/or manufacturing domains.
• Experience working with ontologies, controlled vocabularies or knowledge-graph technologies.
• Experience enabling AI/ML or advanced analytics through well-designed data sets.
• Practical use of AI-assisted development and validation.
• Experience integrating or working with manufacturing, lab or quality systems.
• Experience working with DevOps or platform teams to deploy and operate data and integration services.

Preferred Skills:

• Relevant cloud, DevOps, security, source-control or agile certifications.
• Strong analytical and troubleshooting skills.
• Ability to explain data and ontology concepts in simple terms.
• Clear technical writing and documentation discipline.
• Understanding of secure configuration and audit traceability.
• Ability to collaborate across global teams.
• Continuous-improvement mindset focused on automation and reuse.
• Proficiency in at least one programming language and practical SQL skills.