Design, develop, and optimize scalable data pipelines and architectures to process large and complex datasets, ensuring robustness and efficiency. Integrate, cleanse, and combine data from multiple sources to deliver accurate, high quality datasets, with a focus on performance, reliability and security. Troubleshoot data pipeline issues and implement process improvements. Collaborate with analysts, data scientists and subject matter experts to meet requirements for AI and non-AI related analytics projects. Bachelor's degree in computer science or related field of studies, Master's degree is a plus 3-5 years of experience in data engineering or related role. Profound understanding of concepts in the following areas: Data Architectures, Data Pipelines, Data Warehouses, Data Lakes, Data Governance, Data Integrity and Data Security. Proven expertise on the latest toolsets and trends on data bases, integration and modeling (e.g. Hadoop, Spark, Impala, Denodo, OpenShift) Proficiency in SQL and a general-purpose programming language (e.g. Python) Experience with AI (e.g., using or implementing AI agents) and developing or integrating APIs to interact with LLM applications is a plus. Strong problem-solving, analytical, and attention-to-detail skills. Ability to work independently and communicate effectively with cross-functional teams. We are on a journey to create the best Infineon for everyone. This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills.
