The Digital and Automation Data Integration & Systems Senior Engineer drives and contributes to the reliable, compliant, and efficient use of data across site Digital and Automation environments. The role focuses on focuses on coordinating execution of site-level data strategy, data standards, and system integrations in line with broader network strategies and global standards. The role also enables AI adoption by ensuring data foundations and supporting the deployment and scaling of AI-driven use cases across site operations.

This role drives and contributes to day-to-day execution, lifecycle, and project activities related to data systems, historians, integrations, and local applications. Working closely with system owners, engineering, project teams, validation, and business stakeholders, this role enables and optimises consistent data flows across core platforms while maintaining compliance, validation, and inspection readiness. The Senior Engineer provides technical guidance within defined scope, escalating to the DIS Team Lead where cross-site or strategic alignment is required.

Responsibilities

• Data Strategy, Standards & Governance
  • Coordinate and contribute to the development, documentation, and execution of the site end-to-end data strategy in alignment with network direction.
  • Apply and reinforce data standards, enhancing deployment and adherence to ensure consistency, integrity, and compliance in how data is structured, stored, and used.
  • 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
  • undefined
  • 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.
    • undefined
    • 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
    • undefined

 
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.