Principal Manufacturing Systems Analyst

GSK · Healthcare & Pharma

Bengaluru Luxor North Tower
On-site
Posted today
Apply by 10 Nov
IT & Infrastructure

About the job

About the Team:

Enterprise Systems is the backbone of GSK’s internal operations in Digital & Tech, enabling GSK Global Functions teams such as Finance, Procurement, HR, Legal, Compliance, WREF, CGA and Corporate Secretariat to run seamlessly. This team designs and delivers cutting-edge digital platforms that power critical processes, ensuring efficiency, compliance, and scalability across the enterprise.

Enterprise Systems Management & Business Operations delivers digital solutions that support Enterprise Systems running as a high-performing organisation. This team drives financial discipline, operational rigour and strategic alignment across the ES portfolio that safeguard GSK’s integrity and reputation globally. By joining this team, you’ll help shape systems that support thousands of employees worldwide, driving innovation and reliability in the tools that keep GSK moving forward.

Job Purpose

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

Validation, Quality and technical assurance teams

Other

Technology vendors

System integrators and specialist engineering partners

Managed service and support providers

Basic Qualifications:

Bachelor's or Master's degree in Engineering, Computer Science, Information Technology, Automation, Data, Life Sciences, or a relevant technical discipline.

Minimum 5+ years of experience as a manufacturing systems analyst, business systems analyst, manufacturing-data analyst, MES/LIMS analyst, automation or process-data SME supporting manufacturing or laboratory systems and data environments.

Experience leading manufacturing-systems analysis, requirements gathering, and data-definition activities for a product family, platform, programme, or multiple sites.

Experience reviewing or approving business and functional requirements, process models, data mappings, interface specifications, test scripts, traceability documentation, and validation evidence.

Experience leading functional or data root-cause investigations involving manufacturing systems, interfaces, workflows, master data, and operational records.

Experience coordinating Manufacturing, MSAT, Quality, Laboratory, Data, Engineering, site, and supplier teams through discovery, design, testing, deployment, and stabilization activities.

Experience performing technical risk assessments and defining or tracking mitigations covering security, data integrity, resilience, compliance, and supportability.

Experience coaching engineers or creating reusable standards, patterns, guidance, or knowledge materials based on implementation experience and lessons learned.

Experience preparing or providing technical documentation and evidence for audits, inspections, or formal technical assurance activities.

Experience analyzing data flows and documenting functional requirements, source-to-target mappings, and acceptance criteria between ISA-95 Level 2 systems such as PLC, SCADA, DCS, equipment, instruments, PAT, and historians and Level 3 platforms such as MES/MOM, LIMS/LES, EBR, scheduling, quality, and maintenance systems.

Experience translating Manufacturing, MSAT, CMC, or R&D information needs into documented requirements for Level 3 manufacturing data consumed by Level 5 enterprise, cloud, analytics, data lakehouse, ontology, or knowledge graph platforms, including assessment of data fitness, context, and lineage.

Experience analyzing data structures, semantics, quality, and interface constraints associated with OPC UA, MQTT or Sparkplug B, REST APIs, message brokers/event streaming, SQL, time-series data, and secure file or database exchange, and using that analysis to define requirements or assess interface suitability with technical specialists.

Experience defining manufacturing information requirements and reviewing canonical models, Unified Namespace structures, topic/naming conventions, schema evolution, metadata, and master-data mappings for semantic consistency, traceability, and business use.

Experience defining requirements and mappings that retain batch, material, asset, process, sample, method, timestamp, unit, quality, and provenance context across source and consuming systems.

Experience defining business scenarios and data acceptance criteria for integration, performance, store-and-forward, retry, and recovery testing, and reviewing reconciliation and observability results against defined criteria for data completeness, ordering, timeliness, and integrity.

Experience working with cloud or edge data platforms, data pipelines, version-controlled requirements or mappings, release processes, and operational support activities.

Preferred Qualifications:

LIMS, LES, laboratory instruments, sample/method data.

OPC UA, MQTT, Sparkplug B.

REST APIs, message brokers, event streaming/queues.

UNS (Unified Namespace) , canonical information models, semantic interoperability.

SQL, data profiling, reconciliation and analysis.

Practical scripting capability is desirable.

Manufacturing data flowing to cloud/enterprise platforms.

Scientific metadata, semantic modelling, ontology mapping, knowledge graphs.

Metadata, master data, genealogy, lineage, time-series/event data.

Especially regulated manufacturing/laboratory environments.

Cloud, integration, automation, data, validation, cyber security or engineering certifications.

#AGTech

#GSK-LI

Skills

Application Integrations, Application Programming Interface (API) Security, CI/CD, Cloud Engineering, Configuration Management (CM), Database Management, Data Engineering, Data Integration, Front-End Development, Internet of Things (IoT), Mobile Development, RESTful API Design, Security System Design, Software Development Life Cycle (SDLC), Version Control, Web Development

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

Inclusion at GSK:

As an employer committed to Inclusion, we encourage you to reach out if you need any adjustments during the recruitment process.

Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.

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