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
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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.
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