Description
The Principal 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.
Responsibilities:
- Set up and maintain CI/CD pipelines and integration flows to move digital product profile 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 and collaborate with AI and analytics teams to provision data pipelines, integrations, environments and access patterns.
- 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 / knowledge-graph teams to implement and operate data and metadata structures.
- Design and support integration patterns between PDLM and key downstream systems.
- Make practical use of AI-assisted development, agent-based workflows and prompt templates for engineering, testing, documentation and support.
- Monitor and troubleshoot data pipelines, integrations, environments and related services.
- Document data flows, integration contracts, deployment patterns and runbooks.
- Coach engineers and analysts working on digital product profile, data and integration work.
- Drive continuous improvement in reliability, observability, performance and security for data and integration services.
Basic Qualifications:
- Bachelor's or master's degree in computer science, Information Technology, Software Engineering or a related discipline.
- Minimum 7 years’ experience in data engineering, integration engineering, DevOps or similar roles in complex enterprise or manufacturing environments.
- Experience in designing and delivering data and integration solutions spanning R&D, CMC and/or manufacturing domains.
- Experience in working with ontologies, controlled vocabularies or knowledge-graph technologies.
- Experience in enabling AI/ML or advanced analytics through well-designed datasets, features and integration points.
Preferred Qualifications:
- Apply analytical and troubleshooting skills applied to complex data and integration issues.
- Ability to explain data and ontology concepts in clear, accessible language to non-technical stakeholders.
- Regularly produces and maintains technical documentation.
- Working knowledge of secure configuration, least-privilege access, secret management and audit traceability.
- Experience collaborating across global product, engineering, quality, cyber and service teams.