> Markdown version of [/jobs/ext/3955064-software-dev-engineer-ii-ads-data-manager](https://www.wearedevelopers.com/jobs/ext/3955064-software-dev-engineer-ii-ads-data-manager). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Dev Engineer II, Ads Data Manager - **Company:** Amazon.com, Inc. - **Location:** New York, NY, United States - **Salary:** $158,100.0 - $213,800.0 - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), Amazon Web Services, Software Applications, C Sharp (Programming Language), C++ (Programming Language), Software as a Service, Cloud Computing, Cloud Engineering, Code Review, Computer Programming, Customer Data Management, Software Design Patterns, Distributed Systems, Perl (Programming Language), Machine Learning, Object-Oriented Software Development, Next.js, Software Engineering, Systems Integration, Multithreading, ReactJS, Kotlin, Build Management, Information Technology, Build Process, Software Coding, Stream Processing, Software Version Control, Marketing Cloud - **Published:** October 27, 2026 - **Apply:** https://dejobs.org/x/x/4505A2CD4ED14D8BA298EE3B0D207AA8/job/ ## About the Role * 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 software development engineer or related occupational 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, * 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 ## Description Build the innovative solutions that power Amazon Marketing Cloud's partner ecosystem - ingesting billions of behavioral signals daily at the intersection of massive-scale streaming systems, machine learning, and cloud-native development. You'll develop greenfield services integrating with nearly all advertising business verticals at Amazon while building SaaS integration products for external customers and partners. The Customer Data & Experience team within Amazon Ads works with Professional Services and Tech Integration partners to grow the AMC ecosystem. Our services process billions of signals daily where speed, scale, and accuracy are critical. You'll work across exciting CS domains (massive-scale streaming, ML, data science, cloud-native) and the advertising domain - enabling advertisers, agencies, and SaaS providers to seamlessly integrate and control their experience with Amazon AdTech products. Our tech stack includes native AWS, Kotlin, React.js, and Next.js. If you're energized by working with the latest technologies to massively scale a new product and love discovering the true requirements underlying feature requests, this is your team. Key job responsibilities * Design and build greenfield services that integrate with advertising business verticals across Amazon, enabling partner and SaaS ecosystem growth * Develop and operate massive-scale streaming systems that ingest billions of behavioral signals daily with strict latency and accuracy requirements * Build SaaS integration products for external customers and partners - enabling seamless control of their Amazon AdTech experience * Partner with Professional Services and Tech Integration teams to discover requirements, simplify complex problems, and deliver innovative solutions * Work across the full stack (AWS, Kotlin, React.js, Next.js) to deliver cloud-native, production-quality systems * Collaborate with peers to solve problems spanning machine learning, data science, and large-scale distributed systems