Singapore, Singapore
Onsite
About Global OT & AI Engineering
Global OT & AI Engineering builds the digital foundation that powers Agilent's global manufacturing operations.
Our organization develops enterprise software, AI platforms, cloud-native applications, smart factory technologies, and enterprise data platforms that connect manufacturing sites into one intelligent ecosystem.
Our mission is to transform operational data into trusted insights and intelligent decisions that improve how products are designed, manufactured, tested, and delivered worldwide.
Our portfolio includes:
Manufacturing AI & Advanced Analytics
Global Operations Control Tower
Smart Factory & Industry 4.0
Enterprise Data Platform
Digital Twin Solutions
Manufacturing Knowledge Platform
AI-powered Decision Support
Enterprise Data Exchange Platform
Operational data is one of Agilent's most strategic enterprise assets.
Every day, information flows across ERP, Manufacturing Execution Systems (MES), Product Lifecycle Management (PLM), Quality Systems, Supply Chain platforms, Industrial IoT devices, and engineering applications. The challenge is to create a connected, scalable, and trusted data ecosystem that enables operational excellence and future AI capabilities.
As the Global Operations Data Architect, you will define how enterprise operational data is structured, integrated, governed, and consumed across digital platforms.
Your work will establish the technical foundation supporting enterprise reporting, operational dashboards, AI applications, smart factory initiatives, digital twins, and next-generation manufacturing solutions.
Design and maintain enterprise data architecture supporting Manufacturing, Supply Chain, Procurement, Logistics, Quality, Engineering, and Operational Excellence.
Develop conceptual, logical, and physical data models that promote consistency, scalability, and business alignment.
Define enterprise information models, canonical data structures, and architecture standards.
Ensure data architecture supports current business priorities while remaining adaptable to future digital initiatives.
Define enterprise integration patterns across ERP, MES, PLM, Quality Systems, cloud platforms, and operational technologies.
Establish architecture principles for batch, real-time, and event-driven data integration.
Partner with software engineering teams to promote API-first and reusable integration services.
Support the evolution of enterprise data platforms that enable analytics, AI, and operational reporting.
Collaborate with Data Governance teams to establish enterprise data standards, metadata, lineage, and business definitions.
Support Master Data Management (MDM) and enterprise information governance initiatives.
Promote architecture best practices that improve data consistency, quality, and interoperability.
Ensure enterprise data architectures comply with cybersecurity, privacy, and regulatory requirements.
Design data architectures that enable Artificial Intelligence, advanced analytics, and enterprise reporting.
Collaborate with AI & Data Scientists to ensure enterprise data is accessible, reusable, and AI-ready.
Support the development of semantic models and reusable data products for enterprise digital solutions.
Enable future capabilities such as AI-powered decision support, digital twins, and intelligent operations.
Partner with Enterprise Architects, Software Engineers, Data Engineers, Manufacturing Engineers, and business stakeholders to define technology roadmaps.
Provide technical guidance on architecture decisions and enterprise data standards.
Evaluate emerging technologies and recommend improvements that support Agilent's long-term digital strategy.
Foster a culture of collaboration, innovation, and engineering excellence across global teams.
You'll have opportunities to work with modern enterprise technologies including:
SAP ERP / S/4HANA
SAP ME / MES
PLM
LIMS
Quality Management Systems
Microsoft Azure
AWS
Microsoft Fabric
Databricks
Snowflake
Azure Data Lake
SQL
Python
REST APIs
Event Streaming
Data Factory
Power BI
Tableau
Qlik
We welcome candidates across multiple career stages. Responsibilities and technical leadership will be aligned with your experience and demonstrated capability.
You should have:
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, Data Engineering, or a related discipline.
Experience in Data Architecture, Solution Architecture, Enterprise Data Management, or Data Engineering.
Strong understanding of data modeling, integration architecture, and enterprise information management principles.
Experience working with enterprise applications and cloud-based data platforms.
Strong analytical, communication, and stakeholder management skills.
Passion for designing scalable technology solutions that enable business transformation.
Experience in one or more of the following areas is advantageous:
Manufacturing, Supply Chain, Quality, or Enterprise Operations
Cloud-native Data Platforms
Data Lakehouse or Data Warehouse Architecture
API and Event-driven Architecture
Master Data Management (MDM)
Industry 4.0 or Smart Manufacturing
Artificial Intelligence or Advanced Analytics Platforms
Enterprise Architecture frameworks (e.g., TOGAF)
Additional Details
This job has a full time weekly schedule.Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locationsAgilent Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.