We are a leading chemical company, with the best teams developing intelligent solutions for our customers, and for a sustainable future.

We connect and develop people with diverse talents all over the world. For you, this means a variety of ways to progress.

Not only your performance but also your personality matter to us, regardless of gender, age, ethnicity, orientation, and background.  At BASF, careers develop from opportunities. 

About the Role  

Regional Data & AI Engineer builds and advances a scalable data and AI backbone for smart manufacturing across Asia sites within BASF Coatings. It combines the development of a standardized production data architecture across sites with the ability to translate data into business value through advanced analytics, AI-ML, and agentic AI solutions. The role ensures that production data is consistently leveraged to improve performance, enable better decisions, and drive continuous optimization across the regional manufacturing network.

How You Will Do It  

1. Production Data Architecture
   Define and implement the target architecture for the capture, integration, and provision of production and process data across multiple sites, ensuring scalability and alignment with global standards.
2. IT/OT Integration
   Develop and implement standards and concepts for the integration of production-relevant data sources, including sensors, PLC, SCADA, historian, MES, LIMS, quality, and ERP systems, with a focus on data quality, availability, and cybersecurity.
3. Data Modeling, Analytics and AI Enablement
   Design and structure production data models to support reporting, root cause analysis, process optimization, as well as advanced analytics and AI applications, establishing the foundation for scalable data products.
4. Technical Leadership and Consulting
   Provide technical guidance and advisory support to business functions, production sites, and project teams; translate business requirements into robust architectural solutions and support the implementation of data-driven and AI-enabled initiatives.
5. Standards and Governance
   Establish and maintain regional standards for data models, interfaces, documentation, and governance to ensure consistency, traceability, compliance, and reusability across the organization.
6. Global Collaboration and Continuous Development
   Collaborate within an international network of sites, experts, and stakeholders; contribute to and drive global roadmaps; continuously advance the production data architecture in line with business and technology developments.
7. AI and Agentic AI Solution Development
   Drive the design, development, and industrialization of AI-ML based and agentic AI-based solutions tailored to manufacturing operations, including predictive analytics, intelligent process control, and decision-support systems.
8. External Innovation and Partnerships
   Identify, evaluate, and manage partnerships with external vendors, startups, and technology providers to incorporate advanced, manufacturing-specific AI and digital solutions into the operational ecosystem.

What We Look For  

1. Education: Bachelor’s degree in computer science, data engineering, Data Science / Artificial Intelligence or a comparable scientific or technical field. 
2. Working Experience: 

• Min. 5 years of professional experience in data architecture, data integration, industrial data platforms or advanced analytics, ideally in a global production-related environment.
• Experience in designing scalable data architectures and a good understanding of data quality, governance, information security and standardization.

3. Technical & Professional Knowledge / Others:

• Strong understanding of production processes and industrial system landscapes as well as solid knowledge of integrating IT and OT systems and relevant standards such as ISA-95, OPC or MQTT.
• Strong knowledge of data processing, data modeling and data analysis as well as technologies such as Python, SQL, ETL/ELT concepts and modern data platforms.
• Knowledge of Databricks platform, Agentic AI, Machine Learning techniques, including decision tree learning, clustering, artificial neural networks, etc., and their pros and cons.
• Strong communication and facilitation skills, confidence in working with global stakeholders, a strong team orientation, as well as a high degree of initiative and structuring capability.
• Very good written and spoken Chinese and English skills. 

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