{"id":3485971,"url":"https://alion.io/job/gsk-principal-manufacturing-systems-analyst","title":"Principal Manufacturing Systems Analyst","company":{"id":6649,"name":"GSK","domain":"gsk.com","url":"https://alion.io/company/gsk","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":86,"open_postings":60,"ghost_share":0,"stale_share":0.733,"repost_share":0.017,"time_to_fill_p50_days":16,"computed_at":"2026-11-11T05:49:22Z"}},"role":"Analytics","role_family":"Analytics","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":56000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":702},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Knowledge Graph","optional":false},{"name":"LIMS","optional":false},{"name":"MQTT","optional":false},{"name":"OPC UA","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"CI/CD","optional":true},{"name":"Configuration Management","optional":true}],"status":"closed","first_seen_at":"2026-10-28T00:00:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-11T06:24:27Z","board_verified":false,"closed_at":"2026-11-11T06:24:27Z","days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"About the Team:\nEnterprise 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.\nEnterprise 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.\nJob Purpose\nThe 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.\nThe 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.\nThe 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.\nKey Responsibilities\nAnalyze 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. \nUse 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. \nHold 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. \nLead functional and data investigations across manufacturing systems, escalating promptly where batch execution, product quality, patient supply, data integrity or scientific interpretation may be affected. \nDefine 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. \nAnalyze 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. \nCoach site analysts, engineers, data stewards and super users in manufacturing-system processes, data interpretation, contextualization, testing and issue diagnosis. \nLead manufacturing-systems analysis and data workstreams across multiple projects, releases or sites. \nReview and approve functional requirements, process models, data mappings, interface specifications, test scenarios, traceability and validation evidence for the assigned scope. \nProvide manufacturing-process and data expertise during complex incidents, releases and stabilization, coordinating business SMEs, site teams, technical teams and suppliers. \nAssess functional and data risks and ensure mitigation addresses process control, GxP compliance, data integrity, traceability, usability, resilience and supportability. \nMaintain reusable manufacturing-data definitions, canonical and semantic mappings, ISA-95-aligned models, namespace conventions, business rules, data-quality rules and analysis templates. \nDocument 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. \nDevelop 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. \nSpecify 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. \nPartner 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. \nDefine business and data requirements for completeness, ordering, reconciliation, duplicate handling, late-arriving data, traceability and recovery where connectivity or downstream services may be interrupted. \nEnsure manufacturing-system and data requirements reflect applicable access, segregation, security, privacy, retention, audit-trail and controlled-change expectations. \nLead 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. \nCoordinate business readiness, cutover verification, data reconciliation, hypercare and transition to service, including data ownership, issue triage, support procedures and escalation paths. \nSupport formal technical assurance, audits and inspections and ensure corrective actions are evidence based. \nTranslate lessons from manufacturing-systems analysis and data investigations into improved requirements, data definitions and cross-team analysis practices. \nKey Relationships / Customers\nBusiness and Site Stakeholders\nManufacturing, Quality, Laboratory, Supply Chain and MSAT stakeholders \nSite engineers, automation teams, super users and key users \nBusiness Process Owners and operational risk owners \nDigital & Technology Stakeholders\nProduct Managers and Product Owners \nSolution and Enterprise Architects \nEngineering, DevOps, Data and Integration teams \nService Managers, Cyber Security and Infrastructure teams \nValidation, Quality and technical assurance teams \nOther\nTechnology vendors \nSystem integrators and specialist engineering partners \nManaged service and support providers \nBasic Qualifications:\nBachelor's or Master's degree in Engineering, Computer Science, Information Technology, Automation, Data, Life Sciences, or a relevant technical discipline.\nMinimum 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.\nExperience leading manufacturing-systems analysis, requirements gathering, and data-definition activities for a product family, platform, programme, or multiple sites.\nExperience reviewing or approving business and functional requirements, process models, data mappings, interface specifications, test scripts, traceability documentation, and validation evidence.\nExperience leading functional or data root-cause investigations involving manufacturing systems, interfaces, workflows, master data, and operational records.\nExperience coordinating Manufacturing, MSAT, Quality, Laboratory, Data, Engineering, site, and supplier teams through discovery, design, testing, deployment, and stabilization activities.\nExperience performing technical risk assessments and defining or tracking mitigations covering security, data integrity, resilience, compliance, and supportability.\nExperience coaching engineers or creating reusable standards, patterns, guidance, or knowledge materials based on implementation experience and lessons learned.\nExperience preparing or providing technical documentation and evidence for audits, inspections, or formal technical assurance activities.\nExperience 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.\nExperience 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.\nExperience 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.\nExperience 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.\nExperience defining requirements and mappings that retain batch, material, asset, process, sample, method, timestamp, unit, quality, and provenance context across source and consuming systems.\nExperience 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.\nExperience working with cloud or edge data platforms, data pipelines, version-controlled requirements or mappings, release processes, and operational support activities.\nPreferred Qualifications:\nLIMS, LES, laboratory instruments, sample/method data.\nOPC UA, MQTT, Sparkplug B.\nREST APIs, message brokers, event streaming/queues.\nUNS (Unified Namespace) , canonical information models, semantic interoperability.\nSQL, data profiling, reconciliation and analysis.\nPractical scripting capability is desirable.\nManufacturing data flowing to cloud/enterprise platforms.\nScientific metadata, semantic modelling, ontology mapping, knowledge graphs.\nMetadata, master data, genealogy, lineage, time-series/event data.\nEspecially regulated manufacturing/laboratory environments.\nCloud, integration, automation, data, validation, cyber security or engineering certifications.\n Skills\nApplication Integrations, Application Programming Interface (API) Security, CI/CD, Cloud Engineering, Configuration Management (CM), Database Management, Data Engineering, Data Integration, Front-End Development, Internet of 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