Specialist Data Engineer & AI

Job description

Data Engineering & Architecture Design, develop, and maintain scalable data pipelines, data models, and data products supporting Quality and Manufacturing use cases. Ensure data reliability, availability, scalability, and performance across quality-related analytics solutions. Support data governance, master data management, data lineage, and data quality initiatives across the organisation. Develop, deploy, and monitor machine learning, predictive analytics, and AI models to improve quality performance and operational efficiency.

Apply advanced statistical analysis and AI techniques to identify trends, anomalies, root causes, and predictive quality risks. Participate in AI experimentation, proof-of-concepts, and innovation initiatives aligned with business priorities. Ensure responsible and compliant use of AI solutions according to corporate governance and data privacy requirements. Develop and maintain interactive dashboards, KPI frameworks, and self-service analytics solutions using Power BI and other visualisation tools.

Contribute to digital transformation roadmaps and strategic data initiatives Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related field. One till two years of experience strongly preferred in Data Engineering, Data Science, AI, Business Intelligence, or Advanced Analytics. . Experience in semiconductor, manufacturing, quality management, or industrial environments is preferred.

Experience delivering end-to-end data and analytics solutions from data ingestion through business consumption. Strong programming skills in Python and SQL. Experience with data engineering frameworks, ETL/ELT processes, and modern data architectures. Knowledge of cloud-based analytics platforms such as Azure, AWS, or Google Cloud. Experience with Power BI and enterprise reporting solutions. Experience developing, deploying, and monitoring machine learning models.

Understanding of MLOps, DataOps, CI/CD, and software development best practices. Familiarity with Generative AI, Large Language Models (LLMs), and AI integration patterns is an advantage. Strong understanding of database technologies, data warehousing, and data modelling concepts. Strong analytical and problem-solving capabilities. Ability to translate business challenges into scalable data and AI solutions. Excellent communication and stakeholder management skills.

Experience consulting with business functions and influencing decision-making through data. Strong collaboration skills and ability to work effectively in cross-functional teams. Continuous learning mindset with a passion for innovation and digital transformation. Ability to work in a fast-paced environment and manage multiple priorities. Knowledge of Quality Management systems and methodologies such as ISO 9001, Six Sigma, Statistical Process Control, and FMEA.

Experience with manufacturing execution systems (MES), test systems, or semiconductor data environments. Certification in Data Engineering, Cloud Platforms, AI, or Analytics technologies 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 contact channels and about Diversity & Inclusion at Infineon.