Ensure data-related work is executed in line with applicable quality, validation, cybersecurity, and regulatory requirements, following established SOPs and governance processes.
Contributes to and interprets global data standards for local implementation by providing site operational knowledge
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System Integration & Data Flow Enablement
Design, execute and support core system integrations, ensuring optimised, secure, and compliant data flow and connectivity across system layers
Monitor and support data connectivity, proactively identifying and resolving integration issues, data quality gaps, or performance risks within defined scope, escalating where appropriate.
Execute and improve implementation, configuration, and lifecycle management of site historians and data platforms to enable operational reporting, analytics, and continuous improvement.
Develop, enhance and rationalise local application lifecycle management, including development, configuration, upgrade, enhancements, rationalization, retirement and archiving as well as connectivity to data sources
Maintain accurate asset, configuration, and data mapping documentation to support lifecycle management, validation, and inspection readiness.
Participate in incident, deviation, and recovery activities to ensure timely restoration of services while maintaining data integrity and validated state control.
Provide technical review and guidance on integration and solution design decisions within site scope.
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AI, Analytics & Innovation Enablement
Partner with site operational, process teams and digital innovation teams to implement data-driven use cases, translating business problems into data requirements.
Enable use of data for analytics, AI, and innovation initiatives by ensuring data availability, reliability, and alignment to defined standards.
Support scaling and industrialization of AI and analytics use cases.
Key Attributes, Skills & Competencies
Strong knowledge of data architecture, system integration patterns, and data lifecycle management
Fluent in English and Chinese
Understands and applies data governance and quality principles and their application in manufacturing environments — accuracy, completeness, traceability, and timeliness.
Strong knowledge of GxP data integrity requirements and their implications for manufacturing data systems including digital and automation platforms, and cross-system data flows.
Experience with local application development and system connectivity, with the ability to evaluate and adopt emerging technologies, AI and Automation.
Ability to communicate and collaborate effectively with automation, IT, quality, and business partners to deliver shared outcomes.
Drives a continuous improvement mindset, seeking opportunities to simplify, standardize, and optimize data flows.
Supports and mentors team members in data systems, integration practices, and standards adoption.
Balances performance, compliance, and delivery priorities when designing and implementing solutions.
Preferred Qualifications, Experience & Certifications
Bachelor’s degree in engineering, Computer Science, Information Systems, Life Sciences, or related technical field
2-4 years’ experience in information technology systems/infrastructure or specialist knowledge of process automation/process control systems
1-2 years in a regulated manufacturing environment (pharma or similar preferred)
Experience with Lean/Operational Excellence
Project/program management (PMI, Agile, SDLC) and continuous improvement (e.g., Six Sigma)
IT infrastructure management (e.g., ITIL) and GMP regulatory requirements experience preferred
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Work Location Assignment: Hybrid
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
- To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.
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Information & Business Tech
