Join the Analytics Operations and Programs (AOP) team, a vital group focused on building core analytics, insight generation, and science capabilities for ROW Ops. We specialize in developing scalable analytics applications, AI/ML products, and research models to enhance operational efficiency.

You will collaborate closely with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists, and Business Intelligence Engineers. Utilizing rigorous quantitative approaches, your work will ensure the delivery of high-quality data and science products to a global customer base.

As a Data Engineer, you are central to our mission, responsible for establishing and maintaining the data infrastructure essential for advanced analytics and machine learning solutions. Our team tackles a wide array of scalable challenges across the Rest of the World (ROW), including optimizing operations through real-time signal analysis, last-mile logistics, LLM-driven automation, and advanced pricing models.

Key responsibilities include designing, developing, and maintaining robust data pipelines to support AI/ML model lifecycle, from development through production. You will implement and manage CI/CD pipelines for data and AI/ML solutions, ensuring seamless integration.

Collaborate with data scientists to define and implement efficient data processing strategies based on evolving data requirements. You will also be responsible for creating and overseeing data warehouses and data lakes, adhering to strict data governance and security protocols.

Engage with product managers and business stakeholders to understand their data needs and translate them into actionable technical requirements. Continuously explore emerging technologies and best practices in data engineering to propose innovative improvements to our data infrastructure and processes for AI/ML models and analytics applications. Active participation in code reviews and contributing to team best practices are also key aspects of this role.

We are seeking candidates with hands-on experience in data modeling, data warehousing, and building ETL pipelines. A minimum of three years of dedicated data engineering experience is required.

Proficiency in at least two of the following programming languages is essential: Scala, Java, Python, C/C++, or Go. Familiarity with cloud services such as AWS or equivalent is also necessary, along with experience in version control systems and CI/CD pipeline implementation.

Preferred qualifications include experience with non-relational databases and data stores, as well as expertise in big data technologies. Experience with training and deploying AI/ML systems for large-scale optimizations and data analytics is highly advantageous.