Want to help us build software systems to make the world's best product catalog better?
An information-rich and accurate product catalog is a strategic asset for Amazon. Amazon's Item Authority organization is chartered to establish and protect an unambiguous identity for every product available in our vast catalog as Amazon's systems, processes and our customers depend on having a stable product identity to ensure that the right product arrives at their doorstep.
We are looking for a customer-focused and highly-motivated software development engineer to build software systems that detect catalog items changing their identity over time or representing an inconsistent mix of products. This role will present you an opportunity to work with collaborative leaders, work backwards from customers, identify problems, propose innovative solutions, relentlessly raise standards, and have a positive impact on hundreds of millions of Amazon customers. You will achieve this goal by employing a combination machine learning techniques and data analytics processes at Amazon scale.
* Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
• Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
• 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
• 2+ years of non-internship professional software development experience
• A Bachelor's degree in Computer Science or related engineering fields
• 1-2 years of professional software development experience (Java, C#, and/or C++)
• Proficiency with object-oriented design, data structures, and algorithms
• Strong debugging, troubleshooting, and problem-solving skills
• Ability to deal with ambiguous/undefined problems
• Self-driven and collaborative work ethics
• Excellent verbal and written communication skills
• Experience in Amazon Web Services
• Experience with modern methods for parallelized processing of large, distributed datasets (e.g. Spark, Hadoop, Map-reduce)