AGGP2026 - Graduate Digital Transformation Specialist - PLM Migration Methodology & Industrialization
- Generic Process Definition & Methodology:
- Lead the definition and optimization of generic, reusable processes and methodologies for end-to-end PLM data migration. This includes detailed analysis of diverse legacy helicopter program data and processes and designing standardized future-state workflows adaptable across various programs.
- Develop comprehensive process maps, guidelines, and frameworks for data extraction, cleansing, transformation and validation, ensuring they are scalable and repeatable.
- Data Strategy & Quality:
- Define the methodology for data cleansing and quality assurance for large-scale legacy datasets. Establish rules and governance for data integrity across multiple program migrations.
- Industrialization & Blueprinting:
- Identify opportunities to industrialize the migration lifecycle , focusing on repeatable steps and best practices rather than direct script development.
- Create a robust methodological blueprint for future PLM migrations, including approaches for automation integration (even if developed by others) and intelligent data handling.
- Artificial Intelligence (AI) Exploration:
- Investigate and propose where AI/Machine Learning (ML) methodologies can enhance migration efficiency and accuracy, such as intelligent data classification or anomaly detection within the defined processes.
- Documentation & Knowledge Transfer:
- Develop comprehensive documentation of all migration methodologies, processes and lessons learned. Facilitate extensive knowledge transfer to internal teams for long-term sustainability.
- Master's degree in Engineering, Computer Science, Information Systems, or a related field.
- Experience in digital transformation or large-scale system migration projects , with a strong emphasis on methodology definition and process industrialization is desirable .
- Deep understanding of Product Lifecycle Management (PLM) concepts, processes, and data models , ideally within complex engineering or manufacturing environments (e.g., aerospace, automotive).
- Experience in defining data cleansing, data migration, and data transformation methodologies for complex datasets.
- Expertise in process analysis, re-engineering, and optimization .
- Familiarity with Artificial Intelligence (AI) and Machine Learning (ML) concepts and their potential application to data quality or process optimization.
- Excellent analytical, strategic thinking, and problem-solving skills.
- Exceptional communication and stakeholder management abilities, capable of translating complex technical concepts into clear methodologies.
Airbus Helicopters SAS Employment Type:
Permanent Classe Emploi (France): Classe F12 Experience Level:
Entry Level Job Family:
Programme & Project Management By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to [email protected]. At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.
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