Data Engineer, Digital Supply Chain, ARTC

A*STAR RESEARCH ENTITIES; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading research organization in Singapore is seeking a Data Engineer to develop and maintain data pipelines and support AI research in supply chain analysis and automation. The ideal candidate will have a Master's degree, strong skills in Python and SQL, and experience in cloud environments. This role includes responsibilities such as building data infrastructures and ensuring data quality for AI-driven solutions.

Qualifications

• Strong proficiency in Python and SQL; familiarity with PySpark, Pandas, or Dask is a plus.
• Proven experience building data pipelines in cloud or hybrid environments.
• Hands-on experience with data lakes, data warehousing, or streaming architectures.

Responsibilities

• Design, implement, and maintain scalable ELT/ETL pipelines.
• Perform data wrangling and preprocessing for ML/AI model training.
• Develop containerized and cloud-compatible data solutions.

Skills

Python

SQL

Data pipeline development

Data wrangling

Interpersonal skills

Education

Master's degree in Computer Science or related field

Tools

Airflow

Docker

Kubernetes

AWS

Azure

Job description

The Digital Supply Chain Group at Digital Manufacturing Division at ARTC is seeking a Data Engineer with strong expertise in data pipelines, transformation, and analytics. This role supports ongoing and new AI research efforts focused on supply chain analysis and automation. The successful candidate will play a pivotal role in preparing clean, structured, and timely data to enable AI-driven solutions for real-world supply chain challenges in FMCG, Med-tech, Manufacturing, Aerospace, energy and semiconductor sectors.

Key Responsibilities

1. Build and Maintain Data Infrastructure
   • Design, implement, and maintain scalable ELT/ETL pipelines across diverse data sources (SAP, MES, WMS, ERP, IoT, etc.)
   • Develop automated data ingestion and transformation processes using modern tools (e.g., Airflow, dbt, Kafka, etc.)
2. Data Modeling & Analytics Support
   • Perform data wrangling and preprocessing tailored for ML/AI model training and simulation environments
   • Work with AI scientists to prepare datasets for use in time series forecasting, optimization models, and generative AI
3. Collaborate Across Domains
   • Liaise with domain experts, supply chain analysts, and software developers to understand operational data needs
   • Serve as the bridge between raw data and AI solution pipelines
4. Maintain Data Quality & Governance
   • Implement checks, logging, and alerts to ensure high data reliability and traceability
   • Ensure alignment with FAIR data principles and secure data handling practices
5. Tooling and Deployment
   • Develop containerized and cloud-compatible data solutions (e.g., using Docker, Kubernetes, AWS, Azure)
   • Contribute to end-to-end solution integration with dashboards or digital twin systems

Job Requirements

• Master's degree in Computer Science, Data Engineering, Information Systems, or a related field
• Strong proficiency in Python and SQL; familiarity with PySpark, Pandas, or Dask is a plus
• Proven experience building data pipelines in cloud or hybrid environments
• Familiarity with supply chain data systems (SAP, ERP, MES) and industry-specific data schemas is highly preferred
• Hands-on experience with data lakes, data warehousing, or streaming architectures
• Excellent interpersonal and communication skills; ability to work in cross-functional R&D teams
• Bonus: Familiarity with supply chain KPIs and AI/ML workflows is advantageous

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.