Software Development Engineer, Amazon Brand Store

Amazon Amazon · Big Tech · NY +1 · Software Development

Software Development Engineer role focused on building and maintaining large-scale data processing systems and highly available APIs for Amazon Brand Store. The role involves designing, building, and modernizing complex systems, creating real-time data analytics pipelines, and collaborating cross-functionally to drive architectural decisions. While the team is exploring generative AI, this specific role is centered on data engineering and API development.

What you'd actually do

  1. Design, build, and maintain data processing systems at petabyte scale to support advertiser-facing analytics and reporting
  2. Simplify and modernize complex existing systems to improve reliability, scalability, and developer velocity
  3. Build real-time data analytics pipelines, APIs, and reporting systems that surface the impact of brand stores to advertisers
  4. Own end-to-end delivery of mission-critical analytics infrastructure that directly influences advertiser decision-making and investment
  5. Collaborate cross-functionally with Product Managers, TPMs, SDEs, and senior leaders across the org to define technical direction and deliver on shared goals

Skills

Required

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • 1+ years of Object Oriented Design experience
  • Experience programming with at least one software programming language

Nice to have

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

What the JD emphasized

  • large-scale data processing systems
  • highly available APIs
  • real-time data analytics pipelines
  • mission-critical analytics infrastructure