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.
Less than one year