Global Operations Data Architect — AI & Digital Manufacturing

Agilent Technologies, Inc.; Singapore; Presencial; SGD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work option

Descripción de la vacante

Agilent Technologies, Inc. is seeking a Global Operations Data Architect in Singapore to shape the enterprise data foundation for manufacturing, supply chain, and quality.

You will define data models, integration standards, and information frameworks to enable trusted data and AI-enabled digital manufacturing solutions. You will collaborate with business leaders, software engineers, and data governance teams to build scalable, reusable data architectures across global operations.

Formación

• Design and maintain enterprise data architecture across Manufacturing, Supply Chain, Quality, and Operations.
• Develop conceptual, logical, and physical data models for consistency and scalability.
• Define enterprise information models, canonical data structures, and architecture standards.

Responsabilidades

• Design and maintain enterprise data architecture supporting multiple business domains.
• Define integration patterns across ERP, MES, PLM, and cloud platforms.
• Collaborate with governance to establish standards, metadata, lineage, and definitions.
• Enable AI-ready data and analytics through semantic models and reusable data products.

Conocimientos

Data Modeling

Enterprise Data Architecture

Data Integration

Cloud Platforms

API & Events

Educación

Bachelor's or Master's in CS/IS/Engineering

Herramientas

SQL

Python

REST APIs

ETL Tools

Descripción del empleo

Agilent Technologies, Inc. is seeking a Global Operations Data Architect in Singapore to shape the enterprise data foundation for manufacturing, supply chain, and quality.

You will define data models, integration standards, and information frameworks to enable trusted data and AI-enabled digital manufacturing solutions. You will collaborate with business leaders, software engineers, and data governance teams to build scalable, reusable data architectures across global operations.