The mission of the Advanced Analytics Solution team is to develop and operate end-to-end automation, analytics, and AI assets to enhance company processes and business outcomes. As a Big Data Engineer, the role involves close collaboration with analytics, IT, and architecture teams to develop, industrialize, and maintain data pipelines, analytics/AI models, and automation software for production. Responsibilities also include liaising with the IT department to manage the cloud-based analytics environments utilized by the team. The role encompasses technology scouting and defining solutions and standards for Data & Analytics across the organization, participating in cross-functional working groups at both local and international levels. This position offers a dynamic and innovative work environment with opportunities for professional growth and development. Key Responsibilities: Data Pipeline Development: Design, optimize, and re-engineer data pipelines and analytics models to ensure robust and efficient data processing. Project Delivery: Deliver automation and analytics artifacts in alignment with project timelines and objectives. Cross-functional Collaboration: Participate in cross-functional working groups to represent the Advanced Analytics team and contribute to the definition of target solutions. Cloud Infrastructure Management: Assist team members in managing cloud-based analytics infrastructure in coordination with the IT department. Operational Monitoring: Develop and implement activities required to operate and monitor production projects effectively. Technology Scouting: Support the identification and evaluation of new technologies, techniques, and software within the Data & Analytics domain. Key Requirements/Skills/Experience: Experience: 2 years of experience in engineering, with a focus on developing and operating analytics/AI assets in large-data contexts. Education: Master's degree in Computer Science or Computer Engineering. A PhD or post-graduate courses in related fields (e.g., HPC, BDE, DS) is a plus. Technical Proficiency: Excellent knowledge of Python, PySpark, SQL, and scripting. Proficiency with orchestration tools such as Airflow. Strong software engineering skills. Database Knowledge: Good understanding of relational and non-relational databases, ETL processes, CDC, and data streaming tools and techniques. Cloud Ecosystems: Experience with Microsoft Azure or AWS ecosystems. Big Data Architectures: Familiarity with analytics and Big Data architectures (e.g., Kafka, Hadoop, Databricks) and web/cloud technologies (e.g., Docker, Kubernetes). Language Skills: Fluent in English, both written and spoken. Soft Skills: Team spirit, self-motivation, and a proactive, result-driven work style. Strong ability to meet deadlines, with excellent self-organization. Strong analytical, problem-solving, and communication skills. Additional Knowledge: Familiarity with statistics and data science topics, MLOps techniques, network communication protocols, and project management will be considered a plus. J-18808-Ljbffr