Principal Manufacturing Systems Analyst

Job Summary

The Manufacturing Systems Analyst is the subject-matter expert for manufacturing systems, manufacturing processes and the data generated across shop-floor, laboratory and manufacturing-operations environments. The role develops a detailed understanding of how equipment, automation, historians, MES/MOM, LIMS/LES, PAT and related systems create, transform and consume data, and ensures that information is usable by Manufacturing, MSAT, Quality, CMC and R&D stakeholders.

The role analyses data flows across ISA-95 (International Society of Automation standard 95) Levels 2, 3 and 5 and translates manufacturing and scientific needs into clear requirements, process models, source-to-target mappings, contextualization rules, data-quality controls and acceptance criteria. The job holder works closely with FIL, automation, OT, application, data, cloud and architecture teams, providing the manufacturing-data expertise needed to design integrations and data products that preserve batch, material, asset, process, sample, method, timestamp, unit, quality and provenance context.

The role acts as the bridge between manufacturing and technical teams, supporting discovery, design, testing, deployment, issue investigation, and continuous improvement. It develops reusable manufacturing data definitions, mappings, analysis methods, documentation and training, while promoting consistent interpretation and use of manufacturing data across sites, products and programs.

Key Responsibilities

• Analyze end-to-end business processes, system interactions and data flows across ISA-95 Level 2 equipment and control systems, Level 3 manufacturing operations systems, and Level 5 enterprise, analytics, cloud and R&D platforms.
• Use approved AI tools in your day-to-day work to improve your own productivity and your team\'s ways of working, sharing what works and applying sound judgement, including validating outputs and following GSK\'s Responsible AI, privacy and security requirements.
• Hold mappings, interface definitions and test scenarios under version control, peer-review them before release, and run scripted data-reconciliation and regression checks with the evidence kept with the change.
• Lead functional and data investigations across manufacturing systems, escalating promptly where batch execution, product quality, patient supply, data integrity or scientific interpretation may be affected.
• Define functional interface requirements and detailed manufacturing data mappings for automation, historians, MES (Manufacturing Execution System)/MOM (Manufacturing Operations Management), LIMS (Laboratory Information Management System)/LES (Laboratory Execution System) , PAT (Process Analytical Technology), laboratory instruments, asset systems and enterprise or scientific data platforms.
• Analyze manufacturing records, events, tags, messages, logs, metadata and data-quality results to identify missing context, inconsistent definitions, mapping defects, data loss, duplication, timing issues and opportunities for improvement.
• Coach site analysts, engineers, data stewards and super users in manufacturing-system processes, data interpretation, contextualization, testing and issue diagnosis.
• Lead manufacturing-systems analysis and data workstreams across multiple projects, releases or sites.
• Review and approve functional requirements, process models, data mappings, interface specifications, test scenarios, traceability and validation evidence for the assigned scope.
• Provide manufacturing-process and data expertise during complex incidents, releases and stabilization, coordinating business SMEs, site teams, technical teams and suppliers.
• Assess functional and data risks and ensure mitigation addresses process control, GxP compliance, data integrity, traceability, usability, resilience and supportability.
• Maintain reusable manufacturing-data definitions, canonical and semantic mappings, ISA-95-aligned models, namespace conventions, business rules, data-quality rules and analysis templates.
• Document the functional use, source structures and data semantics of industrial interfaces such as OPC UA, MQTT/Sparkplug B, APIs (Application Programming Interface), message queues, files and databases, and support technical teams in selecting appropriate integration approaches.
• Develop and govern contextualization and semantic mappings from equipment tags and process signals to assets, materials, batches, process steps, samples, methods and products using metadata, master data, ontologies and knowledge-graph-ready relationships.
• Specify and verify how manufacturing and laboratory data must be made available to enterprise and R&D consumers while retaining source, timestamp, unit of measure, quality status, lineage, batch and equipment context.
• Partner with CMC, MSAT (Manufacturing Science and Technology), Data Science and R&D teams to translate scientific and process-analysis needs into scalable integration services and consumable, well-described data products.
• Define business and data requirements for completeness, ordering, reconciliation, duplicate handling, late-arriving data, traceability and recovery where connectivity or downstream services may be interrupted.
• Ensure manufacturing-system and data requirements reflect applicable access, segregation, security, privacy, retention, audit-trail and controlled-change expectations.
• Lead functional risk assessments, requirements of traceability, data verification, user acceptance testing and validation support using a risk-based approach appropriate to GxP and data-integrity requirements.
• Coordinate business readiness, cutover verification, data reconciliation, hypercare and transition to service, including data ownership, issue triage, support procedures and escalation paths.
• Support formal technical assurance, audits and inspections and ensure corrective actions are evidence based.
• Translate lessons from manufacturing-systems analysis and data investigations into improved requirements, data definitions and cross-team analysis practices.

Key Relationships / Customers

Business and Site Stakeholders

• Manufacturing, Quality, Laboratory, Supply Chain and MSAT stakeholders
• Site engineers, automation teams, super users and key users
• Business Process Owners and operational risk owners

Digital & Technology Stakeholders

• Product Managers and Product Owners
• Solution and Enterprise Architects
• Engineering, DevOps, Data and Integration teams
• Service Managers, Cyber Security and Infrastructure teams

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.