{"id":3485974,"url":"https://alion.io/job/gsk-principal-integration-engineer","title":"Principal Integration Engineer","company":{"id":6649,"name":"GSK","domain":"gsk.com","url":"https://alion.io/company/gsk","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":54,"ghost_share":0,"stale_share":0.833,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Legal","role_family":"Legal","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":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"JavaScript","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Least Privilege","optional":false},{"name":"LIMS","optional":false},{"name":"MQTT","optional":false},{"name":"OPC UA","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"TypeScript","optional":false},{"name":"Agile","optional":true}],"status":"live","first_seen_at":"2026-10-28T00:00:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-01T23:11:48Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"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:\nIntegration Engineer provides technical leadership for the design, implementation and lifecycle management of data integrations connecting shop-floor and laboratory systems with site, enterprise and R&D data platforms. The role focuses on ISA-95 (International Society of Automation standard 95) Levels 2, 3 and 5, enabling governed and contextualized data flow from automation and equipment through manufacturing operations systems to enterprise, analytics and scientific environments.\nThe role leads integration across Manufacturing, MSAT (Manufacturing Science and Technology), Quality, Laboratory, CMC and R&D use cases, including Factory Integration Layer (FIL) capabilities, industrial connectivity, event-driven integration, canonical data models, Unified Namespace patterns, APIs and secure cloud or edge interfaces. The job holder ensures solutions preserve manufacturing context, genealogy, data integrity and semantic meaning while aligning with approved architecture, cyber security, validation and engineering standards.\nThe role coordinates automation, OT, IT, data, cloud, application and scientific teams and acts as the technical lead for complex cross-layer delivery and operational issues. It develops reusable interface patterns, engineering standards, test strategies, monitoring and support documentation, and strengthens capability through coaching and knowledge transfer.\nKey Responsibilities:\nLead end-to-end integration design across ISA-95 Level 2 control and equipment systems, Level 3 manufacturing operations systems, and Level 5 enterprise, cloud, analytics 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 \nOwn technical quality for FIL and related integration services, including interface specifications, data contracts, mappings, configuration records, deployment artefacts, test evidence and operational acceptance criteria. \nPerform troubleshooting and root-cause analysis, with timely escalation where manufacturing batches, product quality, patient supply or data integrity may be affected. \nDesign and configure secure interfaces, data pipelines, event streams, APIs and data models that integrate automation, historians, MES (Manufacturing Execution System) / Electronic Batch Record. (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. \nAnalyse message flows, logs, traces, metrics, data-quality controls and system behaviour across edge, site and cloud components to identify defects, latency, data loss, schema drift, performance constraints and opportunities for improvement. \nCoach site engineers and super users and contribute to training, runbooks and knowledge articles. \nLead technical design and implementation across multiple projects, releases or sites. \nReview and approve key technical specifications, design documents, configurations, test scripts and validation evidence. \nProvide technical direction during complex incidents, releases and stabilisation and coordinate internal and supplier engineering resources. \nAssess technical risks and ensure mitigation addresses security, compliance, resilience, data integrity and supportability. \nMaintain reusable integration patterns, canonical models, namespace and topic conventions, API standards, connector templates, deployment automation and engineering guardrails for manufacturing and R&D data integration. \nDefine and implement connectivity patterns for industrial protocols and interfaces such as OPC UA(Open Platform Communications Unified Architecture) MQTT, Sparkplug B, REST APIs (Representational State Transfer Application Programming Interface), message queues, file-based exchange and database integration, selecting patterns according to criticality, latency, security and supportability requirements. \nDevelop contextualization and semantic mapping from equipment tags and process signals to assets, materials, batches, process steps, samples, methods and products using governed metadata, master data, ontologies and knowledge-graph-ready relationships. \nEnable reliable movement of manufacturing and laboratory data to enterprise and R&D consumers while retaining source, timestamp, unit of measure, quality status, lineage, batch and equipment context. \nPartner with CMC, MSAT, Data Science and R&D teams to translate scientific and process-analysis needs into scalable integration services and consumable, well-described data products. \nDesign for store-and-forward, buffering, retry, idempotency, ordering, reconciliation, observability and disaster recovery where connectivity or downstream services may be interrupted. \nApply OT/IT security principles including network segmentation, least privilege, certificate and secrets management, encrypted transport, secure remote access and controlled change across edge, site and cloud boundaries. \nLead interface risk assessments, commissioning, qualification and validation activities using a risk-based approach appropriate to GxP and data-integrity requirements. \nCoordinate integration cutover, data reconciliation, hypercare and transition to service, including service-level measures, alerting, runbooks, ownership boundaries and escalation paths. \nSupport formal technical assurance, audits and inspections and ensure corrective actions are evidence based. \nDrive engineering lessons learned and cross-team continuous improvement. \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 \nArea of Specialization:\nTechnical solution implementation and configuration \nInterfaces, workflows, recipes, data models and environment design \nTechnical specifications, design documentation and validation evidence \nTesting, release, deployment and configuration management \nLogs, metrics, monitoring and root-cause analysis \nSecurity, data integrity, resilience and supportability \nRegulated manufacturing, quality or laboratory technology environments \nTechnical leadership across products, sites or programmes \nDesign assurance and complex technical decision making \nISA-95 Levels 2, 3 and 5 integration architecture and data flows \nFactory Integration Layer and industrial edge integration patterns \nOT protocols and connectivity, including OPC UA, MQTT/Sparkplug B and industrial historians \nMES/MOM, LIMS/LES, PAT, laboratory, asset and automation system integration \nAPI-led, event-driven and message-based integration using governed data contracts \nUnified Namespace, canonical information models and semantic interoperability \nManufacturing data contextualization, genealogy, lineage, time-series and event data \nR&D and CMC data integration, including scientific metadata, ontologies and knowledge graphs \nCloud and edge integration, containerized services, CI/CD (Continuous Integration / Continuous Delivery ) and infrastructure/configuration automation \nIntegration observability, reconciliation, resilience, performance and operational support \nBasic Qualifications:\nBachelor’s or master’s degree in engineering, Computer Science, Information Technology, Automation, Data, Life Sciences, or a relevant technical discipline, or any related technical discipline\nMinimum 7+ years of hands-on technical engineering experience involving enterprise IT, manufacturing OT, automation, data, or integration environments.\nExperience leading the technical design and implementation of solutions across a product family, platform, programme, or multiple sites.\nExperience reviewing or approving technical specifications, design documents, system configurations, test scripts, and technical validation evidence.\nExperience in integrating ISA-95 Level 2 systems such as PLC(Programmable Logic Controller), SCADA(Supervisory Control and Data Acquisition) , DCS (Distributed Control System), equipment, instruments, PAT, or historians with Level 3 systems such as MES/MOM, LIMS/LES, EBR (Electronic Batch Record), scheduling, quality, or maintenance systems.\nExperience integrating Level 3 manufacturing systems and data with Level 5 enterprise, cloud, analytics, data lakehouse, ontology, or knowledge graph platforms supporting Manufacturing, MSAT, CMC, or R&D (Research and Development).\nExperience designing, configuring, or supporting integrations using OPC UA, MQTT(Message Queuing Telemetry Transport) or Sparkplug B, REST APIs, message brokers/event streaming, SQL(Structured Query Language), time-series data, and secure file or database integration.\nExperience creating or implementing canonical data models, Unified Namespace structures, topic/naming conventions, schema evolution approaches, metadata, and master-data mappings.\nExperience designing integrations that maintain batch, material, asset, process, sample, method, timestamp, unit, quality, lineage/provenance, and equipment context between source and consuming systems.\nExperience performing integration and performance testing, data reconciliation and monitoring, and implementing store-and-forward, retry, recovery, or resilience mechanisms in business-critical environments.\nExperience using or supporting cloud and edge platforms, containers, version control, CI/CD, automated deployment, or configuration management.\nExperience developing or maintaining integration components using at least one programming or scripting language, such as Python, Java, C#, or JavaScript/TypeScript.\nExperience performing troubleshooting and root-cause analysis across systems, interfaces, workflows, data, or infrastructure.\nExperience coordinating engineers, site teams, vendors, or specialist partners during design, deployment, cutover, and stabilisation activities.\nExperience conducting technical risk assessments and implementing controls or mitigations covering security, data integrity, resilience, compliance, or supportability.\nExperience coaching engineers or creating reusable engineering materials, such as integration standards, patterns, runbooks, or technical knowledge articles.\nExperience providing technical documentation or evidence for audits, inspections, validation, or formal technical assurance activities.\nExperience applying OT (Operational Technology)/IT security controls to integrations, including network segmentation, 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