Principal Data Engineer

Overview

Provide technical leadership for how product and process data is structured, connected and reused across digital products and manufacturing systems, with a focus on the digital product profile, supporting the flow of product and process data from R&D through CMC into commercial systems.

What you'll do

• Set up and maintain CI/CD pipelines and integration flows to move digital product profile data between PDLM and other systems, using agreed branching strategies and automated checks.
• Keep pipeline, integration and mapping code 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 that enable safe AI proofs of concept and AI-assisted mapping of data models and ontologies, following Responsible AI, privacy and security requirements.
• Own the design of data and integration services within enterprise architecture guardrails, documenting decisions, trade-offs and rationale in decision records and technical documentation.
• Define environment promotion flows (DEV, TEST, VAL, PROD) for data and integration services supporting R&D, CMC and commercial use of product and process data.
• Support releases and integrations end-to-end, maintain pipelines, automate deployments, manage repositories and environments and ensure changes follow validation and change-control requirements.
• Work with R&D and central ontology and knowledge-graph teams to implement and operate data and metadata structures, applying agreed ontologies, reference data and mappings, without owning the ontology roadmap.
• Design and support integration patterns between PDLM and downstream systems such as MES, LES/LIMS, ERP, control and regulatory/CMC platforms.
• Make practical use of AI-assisted development, agent-based workflows and prompt templates for engineering, testing, documentation and support, validating every output for accuracy, security, GxP/data integrity and maintainability.
• Monitor and troubleshoot data pipelines, integrations, environments and related services, including performance and data quality, and drive sustainable remediation for recurring issues.
• Document data flows, integration contracts, deployment patterns and runbooks, keeping them aligned with product and system changes.
• Coach engineers and analysts, and define and maintain data and integration engineering standards, reusable models, patterns and templates.
• Drive continuous improvement in reliability, observability, performance and security for data and integration services, using measures such as data reuse, data quality and time-to-access.

What you'll need

• Bachelor's or master's degree in computer science, Information Technology, Software Engineering or a related discipline, or equivalent practical experience.
• Minimum 7 years' experience in data engineering, integration engineering, DevOps or similar roles in complex enterprise or manufacturing environments.
• Experience designing and delivering data and integration solutions spanning R&D, CMC and/or manufacturing domains, including PDLM or equivalent digital product profile platforms.
• Experience working with ontologies, controlled vocabularies or knowledge-graph technologies to link data across systems, in collaboration with central ontology and data standards teams.
• Experience enabling AI/ML or advanced analytics through well-designed datasets, features and integration points.
• Experience using AI-assisted development, agent-based workflows and prompt templates for engineering, testing, documentation and support, with application of Responsible AI, data privacy, cyber security and GxP controls.
• Experience integrating with or working on manufacturing, laboratory or quality systems (for example MES, LES/LIMS, ERP, control or regulatory/CMC platforms).
• Experience partnering with DevOps or platform teams to deploy and operate data and integration services, including pipelines, environments, monitoring and incident response.

Nice to have

• Relevant cloud, DevOps, security, source-control or agile certifications.
• 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, including records, integration designs and standards.
• Working knowledge of secure configuration, least-privilege access, secret management and audit traceability.
• Experience collaborating across global product, engineering, quality, cyber and service teams.
• Applies continuous-improvement practices focused on automation, reuse and reliable delivery.
• Proficiency in at least one programming language commonly used for data and integration work (for example Python or Java) and practical SQL skills.

Details

• Location: Bengaluru, Luxor North Tower.