Internship - Data Engineering and Backend Engineering

Join our Data Science, Data Engineering & AI team as a Working Student and get hands-on exposure to the data infrastructure and backend services that power real analytics and AI platforms. You will be guided by experienced engineers while contributing to live systems — from building ETL pipelines and writing SQL queries to integrating REST APIs and experimenting with AI-driven automation. This is a learning role with real impact, designed as a stepping stone toward a career in data engineering, backend development, or AI engineering.

Your role

Key responsibilities in your new role

• ETL/ELT Development: Write and test Python ETL scripts and SQL queries to extract, transform, and load data from various sources.

• Data Quality & Monitoring: Assist with data quality validation and monitoring of scheduled pipeline jobs.

• API & Database Integration: Support backend integration tasks by consuming REST APIs and persisting data to databases.

• Engineering Practices (Git): Participate in Git-based workflows (branching, commits, pull requests) following team engineering standards.

• AI-Assisted Automation Prototyping: Help prototype simple AI-assisted automation using LLM APIs alongside experienced engineers.

  Internship Learning Outcomes:

• Data Engineering Foundations: Build practical experience with ETL/ELT pipelines, data modeling, and different data platforms.

• Backend Engineering Skills: Develop backend engineering skills including REST API integration, Python automation, and relational database usage.

• DevOps & Tooling Basics: Learn DevOps fundamentals such as Git workflows, CI/CD awareness, Docker basics, and Linux shell usage.

• LLM & AI-Assisted Development Exposure: Gain hands-on exposure to LLM APIs and AI-assisted development, including prompt engineering and agentic workflows.

• Professional Collaboration: Strengthen collaboration skills through code reviews, technical discussions, and working within an engineering delivery process.

Your profile

Qualifications and skills to help you succeed 

• Educational Background: Enrolled in a Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, or a comparable technical field.
• SQL & Python Proficiency: Able to write Python scripts and basic SQL queries (from coursework or personal projects; no professional experience required).
• Git Familiarity: Familiar with Git basics—cloning, committing, branching, and pushing to a remote repository.
• Curiosity & Learning Mindset: Curious about data engineering and AI tools—interest in how data flows through systems and how LLMs can support engineering work is a strong plus.
• Preferred Intake: January - May 2027, able to commit to a minimum 5-months.

#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.Are you in?

We are on a journey to create the best Infineon for everyone.

We strive to create the best Infineon for everyone by embracing diversity and inclusion. We welcome applicants for who they are and offer a workplace built on trust, openness, respect and equal opportunity.

Our hiring decisions are based on skills and experience. Even if you don’t meet every requirement, we encourage you to apply.

Please let your recruiter know if you need any accommodations during the interview process.

Learn more about our various

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Diversity & Inclusion

at Infineon.

Hillary Woo

https://www.linkedin.com/in/hillary-woo/