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:
Integration 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.
The 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.
The 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.
Key Responsibilities:
- Lead 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.
- 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
- Own technical quality for FIL and related integration services, including interface specifications, data contracts, mappings, configuration records, deployment artefacts, test evidence and operational acceptance criteria.
- Perform troubleshooting and root-cause analysis, with timely escalation where manufacturing batches, product quality, patient supply or data integrity may be affected.
- Design 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.
- Analyse 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.
- Coach site engineers and super users and contribute to training, runbooks and knowledge articles.
- Lead technical design and implementation across multiple projects, releases or sites.
- Review and approve key technical specifications, design documents, configurations, test scripts and validation evidence.
- Provide technical direction during complex incidents, releases and stabilisation and coordinate internal and supplier engineering resources.
- Assess technical risks and ensure mitigation addresses security, compliance, resilience, data integrity and supportability.
- Maintain 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.
- Define 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.
- Develop 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.
- Enable 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.
- Partner 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.
- Design for store-and-forward, buffering, retry, idempotency, ordering, reconciliation, observability and disaster recovery where connectivity or downstream services may be interrupted.
- Apply 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.
- Lead interface risk assessments, commissioning, qualification and validation activities using a risk-based approach appropriate to GxP and data-integrity requirements.
- Coordinate integration cutover, data reconciliation, hypercare and transition to service, including service-level measures, alerting, runbooks, ownership boundaries and escalation paths.
- Support formal technical assurance, audits and inspections and ensure corrective actions are evidence based.
- Drive engineering lessons learned and cross-team continuous improvement.
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
Area of Specialization:
- Technical solution implementation and configuration
- Interfaces, workflows, recipes, data models and environment design
- Technical specifications, design documentation and validation evidence
- Testing, release, deployment and configuration management
- Logs, metrics, monitoring and root-cause analysis
- Security, data integrity, resilience and supportability
- Regulated manufacturing, quality or laboratory technology environments
- Technical leadership across products, sites or programmes
- Design assurance and complex technical decision making
- ISA-95 Levels 2, 3 and 5 integration architecture and data flows
- Factory Integration Layer and industrial edge integration patterns
- OT protocols and connectivity, including OPC UA, MQTT/Sparkplug B and industrial historians
- MES/MOM, LIMS/LES, PAT, laboratory, asset and automation system integration
- API-led, event-driven and message-based integration using governed data contracts
- Unified Namespace, canonical information models and semantic interoperability
- Manufacturing data contextualization, genealogy, lineage, time-series and event data
- R&D and CMC data integration, including scientific metadata, ontologies and knowledge graphs
- Cloud and edge integration, containerized services, CI/CD (Continuous Integration / Continuous Delivery ) and infrastructure/configuration automation
- Integration observability, reconciliation, resilience, performance and operational support
Basic Qualifications:
- Bachelor’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
- Minimum 7+ years of hands-on technical engineering experience involving enterprise IT, manufacturing OT, automation, data, or integration environments.
- Experience leading the technical design and implementation of solutions across a product family, platform, programme, or multiple sites.
- Experience reviewing or approving technical specifications, design documents, system configurations, test scripts, and technical validation evidence.
- Experience 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.
- Experience 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).
- Experience 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.
- Experience creating or implementing canonical data models, Unified Namespace structures, topic/naming conventions, schema evolution approaches, metadata, and master-data mappings.
- Experience designing integrations that maintain batch, material, asset, process, sample, method, timestamp, unit, quality, lineage/provenance, and equipment context between source and consuming systems.
- Experience performing integration and performance testing, data reconciliation and monitoring, and implementing store-and-forward, retry, recovery, or resilience mechanisms in business-critical environments.
- Experience using or supporting cloud and edge platforms, containers, version control, CI/CD, automated deployment, or configuration management.
- Experience developing or maintaining integration components using at least one programming or scripting language, such as Python, Java, C#, or JavaScript/TypeScript.
- Experience performing troubleshooting and root-cause analysis across systems, interfaces, workflows, data, or infrastructure.
- Experience coordinating engineers, site teams, vendors, or specialist partners during design, deployment, cutover, and stabilisation activities.
- Experience conducting technical risk assessments and implementing controls or mitigations covering security, data integrity, resilience, compliance, or supportability.
- Experience coaching engineers or creating reusable engineering materials, such as integration standards, patterns, runbooks, or technical knowledge articles.
- Experience providing technical documentation or evidence for audits, inspections, validation, or formal technical assurance activities.
- Experience applying OT (Operational Technology)/IT security controls to integrations, including network segmentation, least-privilege access, certificate or secrets management, encrypted communication, or secure service-to-service communication.
Preferred Qualifications:
- Experience delivering integrations within regulated pharmaceutical, biopharmaceutical, medical-device, or similarly controlled manufacturing and laboratory environments.
- Relevant technical, cloud, integration, automation, data, validation, cybersecurity, or engineering certifications.
- Deep understanding of ISA-95 Levels 2, 3, and 5, including responsibilities, system boundaries, and integration patterns between these layers.
- Experience with Factory Integration Layer (FIL) and industrial edge integration patterns.
- Experience implementing Unified Namespace (UNS) and semantic interoperability patterns.
- Knowledge of data modelling, ontology mapping, knowledge graphs, master data, metadata, data lineage, and data-product principles.
- Experience contextualizing manufacturing and laboratory data from equipment tags and process signals into assets, materials, batches, process steps, samples, methods, and products.
- Experience supporting Manufacturing, MSAT, Quality, Laboratory, CMC(Chemistry, Manufacturing and Controls), and R&D integration use cases.
- Knowledge of API (Application Programming Interface) management, event streaming, message brokering, schema registries, and interface versioning.
- Experience with industrial historians, MES/MOM, LIMS/LES, PAT, laboratory instruments, asset systems, and automation systems.
- Ability to define non-functional requirements covering latency, throughput, availability, recoverability, scalability, data retention, performance, and supportability.
- Experience with cloud/edge integration, containerized services, deployment automation, and infrastructure/configuration automation.
- Ability to interpret automation/process-control information, tag structures, and historian data and translate them into governed manufacturing and scientific information models.
- Experience bridging manufacturing engineering, automation, data engineering, cloud/IT, and scientific/R&D teams for complex cross-layer integration.
#AGTech
#GSK-LI
Skills
Agile Methodology, API Management, CI/CD, Cloud Based Services, Computer Programming, Configuration Management (CM), Containerization, Database Management, High Availability (Inactive), Infrastructure As Code (IaC), Microservices Architecture, Network Security, Operating Systems (OS), System Monitors, Version Control System
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:
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Please contact our Recruitment Team at IN.recruitment-adjustments@gsk.com to discuss your needs.
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