Global Operations Data Engineer
Agilent Technologies2 months ago
Singapore, SingaporeMid Level
Responsibilities
- Design, develop, and maintain scalable enterprise data pipelines integrating manufacturing, supply chain, procurement, logistics, quality, engineering, ERP, MES, and Industrial IoT platforms.
- Build reusable data products, curated datasets, cloud-native data solutions, and integration services for reporting, analytics, AI applications, and digital products.
- Develop ETL/ELT, batch, streaming, event-driven, API, and enterprise integration solutions across SAP, MES, PLM, quality systems, cloud platforms, and operational technologies.
- Implement automated data quality validation, monitoring, reconciliation, exception handling, metadata, lineage, cataloging, and Master Data Management capabilities.
- Prepare AI-ready datasets and feature engineering pipelines in collaboration with AI and data science teams.
- Monitor and improve the health, availability, performance, observability, logging, and alerting of data platforms and services.
- Apply DevOps and CI/CD practices to automate deployment, testing, and operational support.
- Collaborate with data architects, software engineers, manufacturing, supply chain, quality, engineering, IT, and business stakeholders on enterprise digital transformation initiatives.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, Engineering, or a related discipline.
- Experience in data engineering, software engineering, data integration, or enterprise data platforms.
- Strong programming skills in Python and SQL.
- Experience building and maintaining scalable data pipelines and cloud-based data solutions.
- Understanding of data modeling, ETL/ELT processes, API integration, and enterprise data management principles.
- Strong analytical, problem-solving, and communication skills.
- Preferred experience includes manufacturing, supply chain, quality, enterprise operations, cloud-native data platforms, data lakehouse or warehouse architecture, event-driven processing, data governance, metadata management, MDM, AI or advanced analytics platforms, Industry 4.0, Industrial IoT, smart manufacturing, DevOps, and CI/CD.
Benefits
- Full-time schedule with occasional travel and day shift.
- The role has no specified end date.
- Pay and benefit information varies by country and location; specific pay range details are provided during the hiring process.
- Agilent is an equal opportunity employer.
Tech Stack
Categories
Data Engineering
About Agilent Technologies
Agilent Technologies builds analytical instruments, lab software, diagnostic and genomics solutions, plus consumables and services used by pharmaceutical, chemical, environmental, and clinical labs. It sells systems such as chromatography and mass spectrometry platforms, pathology and molecular diagnostic kits, and supports lab operations through its CrossLab services business. Founded in 1999 and headquartered in Santa Clara, California, Agilent is a public company listed on the NYSE (ticker: A) with global manufacturing and R&D sites.