Senior Laboratory Data Automation ARCHITECT, R&D Therapeutics Discovery

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

R&D Operations

Job Sub Function:

Laboratory Operations

Job Category:

Professional

All Job Posting Locations:

Beerse, Antwerp, Belgium

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more at https://www.jnj.com/innovative-medicine

We are searching for the best talent for Senior Laboratory Data Automation Architect, R&D Therapeutics Discovery in Beerse, Belgium.

The Laboratory Data Automation Architect acts as the keystone of automation projects, ensuring that scientific workflows, hardware deployment, software development, and systems integration are all aligned, defined, and interoperable within Johnson & Johnson’s laboratory infrastructures. This role combines scientific acumen with expert-level capabilities in automation design, platform management, and cross-functional collaboration to deliver integrated, scalable, and compliant automation solutions across modality agnostic Therapeutics Discovery.

Key Responsibilities

Architectural leadership

• Design and govern scalable, robust automated scientific workflows that span hardware, software, data, and networking layers.
• Define critical data entities and data flows to enable seamless transitions between disparate components and future-ready extensions.
• Establish and promote best practices for API/SDK usage, data models, and integration standards across internal and external tools.

Program and project execution

• Lead end-to-end automation initiatives from concept through deployment, validation, and ongoing optimization.
• Align projects with strategic objectives, timelines, budgets, and risk management in a global, matrixed environment.
• Define and maintain platform roadmaps, governance, change control, and documentation.

Hardware and software integration

• Identify and select instrumentation and software solutions based on scientific merit and ease of integration.
• Capably orchestrate the integration of lab instrumentation, high-throughput systems, robotics, ELN/LIMS, MES/OT, and data analytics platforms.
• Oversee system integration, including scheduling software, middleware, APIs, and data exchange protocols.

Data management, security, and compliance

• Ensure data quality, lineage, traceability, security, and compliance (IT/OT security and relevant standards).
• Implement proactive monitoring, diagnostic tools, and maintenance regimes to minimize downtime and risk.
• Develop runbooks, validation plans, and documentation to support audits and inspections.

Vendor and ecosystem engagement

• Engage with hardware and software vendors to define standards, roadmaps, and interoperable solutions.
• Communicate industry standards to drive external development toward aligning with J&J needs and the broader industry.

Leadership and collaboration

• Lead and develop global, cross-functional teams (engineering, IT, data science, research, and operations) in a matrix setting.
• Foster an automation-centred culture, supporting internal & external staff, and promoting continuous learning.
• Build strong partnerships with internal stakeholders and external partners to accelerate impact.

Innovation and capability building

• Stay current with emerging automation technologies, data architectures, and analytics methods.
• Explore opportunities in cloud, edge, AI/ML, digital twin, and advanced analytics to enhance scientific workflows.

Documentation and knowledge management

• Maintain com