Data Engineer Job at ASML (Shanghai)

Job Description

ASML Customer Support (CS) Diagnostics is at the core of ASML’s ambition to significantly reduce diagnostic labor hours, improve system availability, and enable predictive and self-healing service capabilities towards 2030. The Data Engineering Engineer who will play a key role in building, scaling, and operationalizing AI-driven diagnostics, observability, and predictive maintenance solutions. This role goes beyond tooling or automation: you will own the full lifecycle of data and AI solutions that directly impact diagnostic accuracy, MTTR, MTBF, and service efficiency. And you will work at the intersection of machine data, diagnostics domain knowledge, and advanced analytics, collaborating closely with CS Diagnostics, Field, D&E, and central platform teams

Job Responsibility

Design, develop, deploy, and maintain machine learning and deep learning models for Predictive Maintenance (PdM), Fault Detection & Classification, and root-cause identification and observability improvement
Own the end-to-end model lifecycle
Continuously improve model performance based on field feedback, diagnostic outcomes, and new data availability
Design and implement scalable, cloud-native data pipelines to ingest, transform, and provision large volumes of structured and unstructured machine data
Work with platforms such as Azure, Databricks, Spark, and Kusto to ensure reliable, performant, and secure data access
Ensure data quality, traceability, and reproducibility for downstream analytics and AI applications
Enable early access to data through proof-of-concept pipelines
Improve observability through machine data by identifying gaps, defining required signals, and translating diagnostic needs into data and model requirements
Identify structural improvements in diagnostic services
Define and follow standards, policies, and protocols for data, models, and analytics solutions
Ensure solutions are compliant, manageable, scalable, and secure
Translate technical outcomes into measurable service impact
Communicate results, insights, and recommendations to senior stakeholders and leadership
Provide guidance and knowledge sharing to colleagues and stakeholders

Requirements

Master's degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field
5+ years of relevant experience in data science, data engineering, or advanced analytics roles
Strong proficiency in Python and experience with analytical and ML libraries
Scripting skill such as PERL, Bash, Power Shell
Proven experience developing and deploying machine learning / deep learning models in production environments
Strong experience with cloud-based data platforms (Azure preferred), including Databricks, Spark, SQL / Kusto
Experience with SQL ETL processes
Solid understanding of statistics, data analysis, SPC/FDC concepts, and analytical problem solving
Experience working with large-scale, high-frequency data streams

Nice to have

Experience with diagnostics, manufacturing, equipment data, or industrial systems
Familiarity with ASML machine data and CS diagnostics workflows
Experience improving observability, fault detection, or predictive maintenance in complex systems
Experience working with business stakeholders and explaining technical results to non-technical audiences
Experience training others and creating technical documentation or user manuals

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