Key Responsibilities  Assist in the development and implementation of data governance frameworks, particularly focusing on data quality and validation.  Work on extracting, transforming, and loading (ETL) data from ERP, Machine, and Quality systems into centralized databases.  Engage in cloud computing initiatives, supporting the management of data storage and computational resources across cloud platforms.  Apply AI and machine learning techniques for data cleaning, validation, and optimization.  Contribute to the certification and standardization of data, ensuring compliance with both internal and external regulations.  Collaborate with cross-functional teams to understand and meet data needs.  Participate in the development and maintenance of data pipelines for efficient data processing.  Support the documentation, reporting, and auditing of data governance activities.

Person Specifications  Currently pursuing or recently completed a Diploma in AI and Data Engineering, or related field.  Understanding of data governance principles, with a focus on data quality and validation.  Experience or knowledge in handling data from ERP systems.  Familiarity with cloud computing environments and services (ex: AWS, Azure, Databricks).  Basic knowledge of AI and machine learning applications in data processing.  Proficiency in data analysis and ETL tools (e.g., Python, SQL, Talend).  Strong analytical and problem-solving skills.  Effective communication skills and ability to work in a team.  Attention to detail and commitment to data accuracy and integrity. Learning Opportunities:  Hands-on experience in data engineering tasks within a global data governance framework.  Exposure to state-of-the-art cloud computing and AI technologies.  Skill development in managing and certifying large-scale data sets.  Mentorship from seasoned data governance and data engineering professionals.  Contribution to high-impact projects in a multinational environment.