Data Engineer

Role overview

Engineering and integration

• Build and maintain CI/CD pipelines and integrations between PDLM and other systems; keep code version-controlled, tested, and peer-reviewed.
• Design data and integration services, define environment promotion flows, automate deployments, and support validated releases and change control.
• Implement agreed ontologies, reference data, metadata, and mappings to link and reuse product profile data across platforms.
• Integrate PDLM with MES, LES/LIMS, ERP, control, and regulatory/CMC platforms.
• Monitor and troubleshoot services, performance, and data quality; improve reliability, observability, performance, and security.
• Document data flows, integration contracts, deployment patterns, runbooks, decisions, and standards.
• Coach engineers and analysts, maintain engineering standards, and develop reusable models and patterns.

AI and data practices

• Use approved AI tools and AI-assisted development workflows for engineering, testing, documentation, and support.
• Validate AI outputs for accuracy, security, GxP/data integrity, privacy, and maintainability before committing or releasing them.
• Collaborate with AI and analytics teams to support safe proofs of concept and AI-assisted data-model and ontology mapping.

Qualifications information

• The description is truncated immediately after the Basic Qualifications heading, so no specific candidate qualifications are available in the provided text.