Data Engineer, Digital Supply Chain, ARTC

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 Build and Maintain Data InfrastructureDesign, 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.) Data Modeling & Analytics SupportPerform data wrangling and preprocessing tailored for ML/AI model training and simulation environmentsWork with AI scientists to prepare datasets for use in time series forecasting, optimization models, and generative AI Collaborate Across DomainsLiaise with domain experts, supply chain analysts, and software developers to understand operational data needsServe as the bridge between raw data and AI solution pipelines Maintain Data Quality & GovernanceImplement checks, logging, and alerts to ensure high data reliability and traceabilityEnsure alignment with FAIR data principles and secure data handling practices Tooling and DeploymentDevelop 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 systemsJob 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 advantageousThe 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.