Principal Integration Engineer

Gsk India; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

GSK’s Enterprise Systems team seeks an Integration Engineer to lead the design, implementation and lifecycle management of data integrations across shop-floor and enterprise data platforms. The role focuses on ISA-95 Levels 2, 3 and 5, enabling governed data flow from automation to enterprise analytics and R&D environments.

You will coordinate cross-functional teams, define integration standards and ensure security, resilience and traceability across edge, site and cloud components.

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 productivity and team workflows, 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, MES, LIMS, LES, PAT, laboratory instruments, asset systems and enterprise data platforms.
• Analyse message flows, logs, traces, metrics, data-quality controls and system behaviour to identify defects, latency, data loss, schema drift and performance constraints.
• 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 conventions, API standards and guardrails for manufacturing and R&D data integration.
• Define and implement connectivity patterns for industrial protocols and interfaces such as OPC UA, MQTT, REST APIs, message queues and database integration.
• Develop contextualization and semantic mapping from equipment tags to assets, materials, batches and products using governed metadata and ontologies.

Job description

Job Summary

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