Lead Engineer, Shopping Product Graph, Data Infrastructure

Job description

Set the technical outlook and design the data infrastructure to support the necessary scale, resilience, and rich feature set that clients depend on. Write robust code to solve ambiguous, large-scale problems. Enable fast iterations on product graph quality through data-driven decision-making supported by experiments and evaluations. Collaborate closely with cross-product area partners to leverage their expertise and infrastructure, translating techniques into tangible, real-world product impact. Work with other engineering leads, Product Managers, and executives to identify areas for further improvement in the broader shopping graph, ensuring all relevant domains align seamlessly. Guide and mentor executive developers and technical leads, elevating the overall technical competency of the organization. Minimum Qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in machine learning architecture. Experience with graph storage and knowledge base systems. Experience with data pipeline infrastructure and quality. Experience leading engineering velocity and experimentation. Preferred Qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 8 years of experience with data structures and algorithms. 5 years of experience in a technical leadership role leading project teams and setting technical direction. 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. Experience with knowledge engineering.