Data Platform Engineer, R&D
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What you'll do
- 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.
- 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
- 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
What they're looking for
- 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.
Nice to have
- 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
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Job Location
SINGAPORE TC-BIOPOLISJob 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
Job Qualifications
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.
Preferred Qualifications
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.
Job Schedule
Full timeJob Number
R000159381Job Segmentation
Experienced ProfessionalsCompany
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