About this role
We are looking for a (Senior) Data Quality & Automation Engineer to build reliable, scalable data foundations for R&D. You will work with complex semiconductor data (wafer, sample, measurement, process) and help enable digital twins, advanced analytics, and efficient execution by making data trusted, traceable, and automated. Key responsibilities - Define and evolve data models for R&D entities - Design and implement robust data pipelines and automated data quality checks - Improve traceability and metadata management so data can be understood, trusted, and reused across teams - Help establish engineering standards for data handling, testing, monitoring, versioning, and documentation - Support the development of scalable digital twin, analytics, and workflow automation use cases by ensuring data is fit for purpose - Evaluate, prototype, and decide when to apply AI/ML vs. rule-based approaches in production data pipelines, balancing impact, complexity, and maintainability What you bring - University degree in Computer Science, Engineering, Physics, Chemistry or a related field - Relevant professional experience in building production-grade systems (3-5 years for Middle, 5-8 years for Senior) - Strong experience in data engineering, backend, and software engineering - Hands-on skills in Python, SQL, APIs, and data pipelines - Proven ability to design reliable pipelines and automate validation of complex data - Strong understanding of data quality, traceability, schema design, and maintainability - Experience with workflow automation, dashboarding, or integrating engineering data into operational/project processes - Experience with testing, monitoring, and production-grade engineering practices - Ability to work in ambiguous environments with imperfect processes and legacy systems - Strong communication skills in English and German, with the ability to collaborate effectively with engineers, researchers, and project stakeholders Nice to have - Experience with semiconductor, manufacturing, lab, metrology, test, or scientific data - Experience implementing AI/ML pipelines in real production environments What matters most You bring a strong data and software quality mindset. You build solutions that are robust, testable, maintainable, and trusted by engineers and project teams. What Nexperia offers - Real-world, complex data challenges in semiconductor engineering - Opportunity to build data-driven and digital twin solutions at scale - Collaborative, international environment with strong engineering focus