Scalable Scientific Data Platform Engineer

Procter & Gamble; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Procter & Gamble located in Singapore is seeking an experienced data engineering professional to build and operate scalable scientific data pipelines that connect diverse data types, from omics to formulation, for analytics and AI discovery.

You will own data pipelines, governance, and interfaces, ensuring reliable data availability and operational support across analytics platforms within a complex scientific data foundation.

Qualifications

• Bachelor's/Master's/PhD in Computer Science, Data Engineering, Software Engineering, or a related field.
• Strong hands-on experience building data pipelines, integrations, and scalable data services.
• Proficiency in Python, SQL, or comparable data-engineering technologies.

Responsibilities

• Engineer Scientific Data Pipelines: Build scalable pipelines to ingest, transform, standardize, and connect scientific data.
• Implement Trusted Data Controls: Implement metadata, provenance, versioning, identity resolution, access, and data-quality controls.
• Operate Scalable Data Services: Build and maintain interfaces among repositories, knowledge graphs, analytical tools, computational models, and AI workflows.

Skills

Python

SQL

Data pipelines

Cloud platforms

APIs

Data quality

Metadata provenance

Education

Bachelor/Master/PhD in CS/Data Eng/SE

Job description

Procter & Gamble located in Singapore is seeking an experienced data engineering professional to build and operate scalable scientific data pipelines that connect diverse data types, from omics to formulation, for analytics and AI discovery.

You will own data pipelines, governance, and interfaces, ensuring reliable data availability and operational support across analytics platforms within a complex scientific data foundation.