The student, as part of the Master Data team will assist the HoD / Digitalisation Team Lead in running departmental digitalisation transformation projects, including but not limited to the implementation of AI agents for supply chain & analytical use cases, data centralisation development as well as research-based work.
Your RoleKey responsibilities in your new role
- AI Agent Development: Prototype an AI agent to analyze supply chain datasets, detect anomalies and data quality issues, and support root-cause analysis and resolution workflows under mentorship from senior engineers.
- Data Virtualization & Integration: Create unified data views through virtualized or semantic layers that centralize data objects from multiple enterprise systems and databases into a single governed source for consistent, self-service analytics.
- Rule-Based Management Support: Assist the project lead in implementing Rule Based Management Systems in Infineon’s Global Master Data applications by defining maintenance processes, validation and derivation rules, and approval workflows while validating results and tracking issues in Jira/Octane.
- Data Analysis & Profiling: Conduct supply chain and Product Master Data analysis using SQL, Python (Pandas), and Excel to assess data completeness, consistency, uniqueness, and accuracy, and produce profiling reports highlighting issues such as missing attributes, duplicate products, and inconsistent routes.
- Digital Transformation Support: Contribute to internal communications and engagement activities related to departmental digital transformation initiatives as part of the project office.
- Data Governance & Quality Management: Ensure ongoing data quality and governance by defining executable data quality rules, monitoring KPIs through Tableau dashboards, and maintaining documentation and change logs in
Internship Learning Outcomes:
- Master Data Knowledge: Understand master data domains and processes (e.g., product, planning, materials) and how they enable business and manufacturing operations.
- Data Engineering & Visualization: Gain hands-on skills in data profiling, mapping, and transformations; configure and test data in Global Master Data applications; visualize data quality using BI tools such as Tableau, SAP BO, or Denodo.
- Testing & Governance: Build testing and governance capabilities by writing UAT scripts, performing fit–gap analysis, monitoring data quality KPIs, and maintaining comprehensive documentation.
- Professional Development: Strengthen analytical, communication, project management, and problem-solving skills through cross-functional collaboration and clear, structured documentation.
- AI Implementation Experience: Gain practical experience in deploying AI agents for real-world supply chain use cases.
- Global Project Exposure: Participate in global initiatives within a leading semiconductor company, gaining insight into international operations and best practices.
Your ProfileQualifications and skills to help you succeed
- Education: On track to attain a Bachelor’s degree in Computer Science, Data Analytics, Engineering, or a relevant field.
- Preferred Technical Skills: Familiarity with Python, Generative AI (GenAI), Tableau, SAP BO, Denodo; HTML knowledge is a plus.
- Preferred Intake: January 27 - May/ June 27
Contact: Hillary Woo
#WeAreIn for driving decarbonization and digitalization.
As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.
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