Data Modeler

Louis Dreyfus Company is a leading merchant and processor of agricultural goods. Our activities span the entire value chain from farm to fork, across a broad range of business lines, we leverage our global reach and extensive asset network to serve our customers and consumers around the world. Structured as a matrix organization of six geographical regions and ten platforms, Louis Dreyfus Company is active in over 100 countries and employs approximately 18,000 people globally. Develop, maintain, and optimize ETL pipelines. Design and implement robust data pipelines in Python, focusing on scalability, performance, and reliability. Schedule and automate workflows, enhancing operational efficiency and accuracy. Collaborate in the development and maintenance of cloud-based infrastructure, applying best practices in DevOps to ensure high data availability and scalability. Work closely with data scientists, quantitative researchers, and trading teams to understand their data needs, providing technical solutions that enable effective data analysis and strategy implementation. Ensure code quality and maintainability by implementing strong CI/CD practices, code versioning, automated tests, and conducting thorough peer-reviews. Stay current with emerging trends and advancements in software development, data engineering, and cloud technologies, integrating new tools and techniques where beneficial. Expertise in handling and optimizing relational databases to support analytical applications Graduation in compute engineering and Equivalent. (BSc or MSc in Computer Science, Engineering, Information Systems, or a related field.) 1 to 2 years of experience with right skillset. Proficiency in Python programming and experience with software development best practices. Knowledge of ETL processes and familiarity with data modeling and warehousing. Experience with Jenkins or tools, and strong understanding of CI/CD principles. Hands-on experience with cloud technologies and services, pr