Global Operations Data Engineer: AI-Ready Data Platform

Agilent Technologies, Inc.; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

Agilent Technologies, Inc. in Singapore is seeking a Global Operations Data Engineer to design, develop, and maintain scalable enterprise data platforms that power operational analytics and AI-enabled decision making.

You will build end-to-end data pipelines across manufacturing and supply chain, implement data governance, expose trusted data via APIs, and collaborate with data scientists and software engineers to deliver digital manufacturing solutions.

Qualifications

• Bachelor’s or Master’s in CS/Data Engineering/related field.
• Experience in data engineering, software engineering, data integration, or enterprise data platforms.
• Strong Python and SQL, SQL-based data modeling, ETL/ELT concepts.
• Experience building scalable data pipelines and cloud-based data solutions.
• Knowledge of APIs, data governance, and enterprise data management.

Responsibilities

• Design, develop, and maintain scalable enterprise data pipelines across multiple domains.
• Build reusable data products and curated datasets for analytics, AI, and reporting.
• Implement cloud-native data solutions with governance, lineage, and quality controls.
• Expose trusted data via APIs and enterprise services; collaborate with software and AI teams.
• Support data governance, metadata, MDM, and data quality monitoring.

Skills

Python

SQL

Data Engineering

ETL/ELT

API Integration

Analytics

Problem Solving

Communication

Education

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

Tools

Apache Spark

dbt

Azure

AWS

Azure Data Lake

Snowflake

Apache Kafka

Data Factory

SAP ERP / S/4HANA

Job description

Agilent Technologies, Inc. in Singapore is seeking a Global Operations Data Engineer to design, develop, and maintain scalable enterprise data platforms that power operational analytics and AI-enabled decision making.

You will build end-to-end data pipelines across manufacturing and supply chain, implement data governance, expose trusted data via APIs, and collaborate with data scientists and software engineers to deliver digital manufacturing solutions.