Lab Informatics Lead

In this role, you lead the development and deployment of robust lab digital infrastructure to enable seamless data exchange between instruments and enterprise informatics systems. You will work across R&D labs in the UK and US, collaborating with IT, data science and scientific teams to design scalable interfaces and data pipelines. The position focuses on automating data capture, contextualization and storage, with opportunities to influence long-term digital strategy and tech transfer. This is a hands-on, cross-functional role that supports compliant, efficient lab operations and data integrity at scale.

• Design, implement, and maintain secure IT/OT interfaces between lab instruments and informatics systems (ELN, LIMS, SDMS)
• Collaborate with IT, Data Science and scientific teams to identify integration needs and define real-time or scheduled data transfer architectures
• Develop or configure middleware, APIs, and custom connectors with internal or external vendors to enable automated data capture and storage
• Manage instrument network connectivity (OPC-UA, MQTT, REST APIs, TCP/IP) and data pipelines from edge to cloud/on-prem environments
• Support system validation efforts (CSV, 21 CFR Part 11) with QA and IT Compliance, plus troubleshoot connectivity and data integration issues
• Contribute to long-term digital strategy for lab automation, analytics, and operational efficiency; assist scale-up and tech transfer to other operational areas as needed
• Participate in required Lonza training programs

• Bachelor’s or Master’s degree in Computer Science, Engineering, Scientific or related field
• Experience in IT/OT integration or lab informatics/digitalisation in biotech, pharma, or CDMO environments
• Hands-on experience integrating lab instruments with ELNs, LIMS, SDMS or similar data systems
• Proficiency with data integration technologies and protocols: OPC UA, MQTT, REST/SOAP APIs, SQL, Python
• Familiarity with lab automation platforms (e.g., Tecan, Hamilton, Agilent, Beckman, Sartorius) and related data workflows
• Knowledge of GxP, 21 CFR Part 11, and data integrity principles (plus)

• collaboration across IT, data science and scientific teams
• strong problem-solving and troubleshooting abilities
• clear communication and stakeholder management
• OPC UA
• MQTT
• REST/SOAP APIs