Data Platform Engineer, R&D

Procter & Gamble I'ntl Operations SA Singapore Branch; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Procter & Gamble I'ntl Operations SA Singapore Branch seeks a skilled data engineer to build and operate scalable scientific data pipelines that connect diverse datasets across biology, OMICS, formulation, and consumer insights. You will own data interfaces, metadata, and data quality controls to enable analytics, AI‑driven discovery, and reliable decision making.

The role requires hands-on Python and SQL experience, cloud familiarity, and a focus on data governance and operational reliability.

Qualifications

• Strong hands-on experience building data pipelines and scalable data services.
• Proficiency in Python, SQL, or comparable data-engineering technologies.
• Experience with structured and unstructured data, databases, APIs, and cloud environments.
• Understanding of metadata, provenance, data quality, versioning, and access controls.
• Familiarity with orchestration, data lakes/warehouses, lakehouses, and cloud platforms.
• Experience leveraging semantic models, ontologies, and knowledge graphs for data discovery.
• Background in biological/OMICS or complex scientific data is a plus.
• Experience building data foundations for analytics, ML, or AI projects.

Responsibilities

• Engineer Scientific Data Pipelines to ingest, transform, and connect data.
• Implement trusted metadata, provenance, and data quality controls.
• Operate scalable data services and maintain interfaces across repositories and tools.

Skills

Data pipeline design

Python

SQL

Cloud platforms

Knowledge graphs

Data governance

Operational reliability

APIs

Orchestration

MLOps / AI workflows

Education

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

Tools

APIs

Cloud platforms

Knowledge graphs

Job description

Overview of role

You will have the opportunity to build and operate the scalable scientific data foundation connecting consumer, biological, OMICS, assay, formulation, and performance data. You will be responsible to deliver reliable, traceable, and scalable pipelines and services that reduce manual handling and provide trusted data for analytics, computational biology, predictive modeling, and AI-supported discovery.You will own data pipelines, interfaces, technical controls, data availability, reliability, operational support, and scalability. If this sounds exciting to you, read on!

Key Responsibilities

1. Engineer Scientific Data Pipelines

• Build scalable pipelines to ingest, transform, standardize, and connect scientific data.
• Integrate laboratory, OMICS, imaging, assay, phenotype, formulation, consumer, and performance datasets.
• Automate data movement into governed analytical environments.
• Translate approved data-product requirements into maintainable technical designs.

2. Implement Trusted Data Controls

• Implement metadata, provenance, versioning, identity resolution, access, and data-quality controls
• Maintain traceability to samples, methods, experimental conditions, transformations, and source systems
• Implement approved semantic and ontology requirements
• Test transformations, interfaces, and controls for reliable downstream use

3. Operate Scalable Data Services

• Build and maintain interfaces among repositories, knowledge graphs, analytical tools, computational models, and AI workflows
• Monitor data availability, pipeline performance, failures, and dependencies
• Resolve bottlenecks affecting data access, reuse, and analytical readiness
• Own operational support and reliability for pipelines, interfaces, and data services

• Bachelors, Masters or PhD degree 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.
• Experience with structured and unstructured data, databases, APIs, and cloud-based environments.
• Understanding of metadata, provenance, data quality, versioning, access controls, testing, and operational support.

• Familiarity with orchestration, data lakes, warehouses, lakehouses, APIs, and cloud platforms
• Experience implementing semantic models, ontologies, knowledge graphs, or FAIR data practices
• Experience engineering biological, OMICS, imaging, laboratory, healthcare, or complex scientific data
• Experience building data foundations for analytics, machine learning, or AI

About us

We produce globally recognized brands and we grow the best business leaders in the industry. With a portfolio of trusted brands as diverse as ours, it is paramount our leaders are able to lead with courage the vast array of brands, categories and functions. We serve consumers around the world with one of the strongest portfolios of trusted, quality, leadership brands, including Always®, Ariel®, Gillette®, Head & Shoulders®, Herbal Essences®, Oral-B®, Pampers®, Pantene®, Tampax® and more. Our community includes operations in approximately 70 countries worldwide.

Visit http://www.pg.com to know more.

Our consumers are diverse and our talents - internally - mirror this diversity to best serve it. That is why we’re committed to building a winning culture based on Inclusion and our ideal candidate is passionate about the same principle: you will join our daily effort of being "in touch" so we craft brands and products to improve the lives of the world’s consumers now and in the future. We want you to inspire us with your unrivaled ideas.

We are committed to providing equal opportunities in employment. We do not discriminate against individuals on the basis of race, color, gender, age, national origin, religion, sexual orientation, gender identity or expression, marital status, citizenship, disability, veteran status, HIV/AIDS status, or any other legally protected factor.