Staff Software Engineer, Ads Growth

As a Staff Software Engineer for Ads Growth at Coupang, you’ll take on the exciting task of designing and developing a large-scale recommendation pipeline. Your job is to empower advertisers through intelligent recommendations, optimizing their budget allocation and ensuring the maximum effectiveness of their campaigns. You'll work with vast amounts of data in a distributed environment, creating low-latency service APIs that facilitate Coupang's rapid growth.

To be considered for the Staff Software Engineer position for Ads Growth at Coupang, you’ll need a Master’s degree in fields like Computer Science or Engineering, coupled with over 5 years of extensive experience in fundamental algorithms, system design, and building large distributed systems. Additionally, proficiency in Java, Spark, and SQL is essential, alongside hands-on experience with large-scale data infrastructure.

In the role of Staff Software Engineer for Ads Growth at Coupang, you’ll be using a variety of technologies. You'll be primarily coding in Java and Spark while working closely with SQL for data management. Familiarity with AWS and understanding of service-oriented architecture will also be beneficial as you build and maintain scalable solutions.

While direct experience in advertising systems is not strictly necessary, having a solid understanding or previous exposure to advertising technologies, search advertising, and recommendation systems can significantly enhance your suitability for the Staff Software Engineer role at Coupang. We value innovative thinkers who can leverage their skills in new domains.

Coupang boasts a vibrant company culture that merges startup energy with the backing of a successful global entity. The Ads Growth team thrives on collaboration and creativity, encouraging every member to drive new initiatives and innovations. You can expect an environment that values bold ideas and fosters personal and professional growth.

When answering this question, highlight specific projects where you designed or maintained distributed systems. Discuss the challenges you faced, how you approached them, and any technologies you used such as Spark or AWS that helped you manage data across multiple servers.

In your response, consider discussing various methods like algorithmic enhancements, caching strategies, and how you would analyze user data to improve recommendations. Citing past experiences and the metrics you used to measure improvement will showcase your capability.

Discuss your systematic approach to debugging, whether it involves logging, testing hypotheses, or using debugging tools. Mention specific examples where your troubleshooting led to significant resolutions or optimizations in your previous projects.

Use this opportunity to give a detailed account of your coding experience in these languages. Share examples of projects you've worked on that required Java and Spark, emphasizing how they relate to big data processing or real-time data analytics.

Research Coupang's business model, focusing on their customer-centric approach and innovations in delivery and services. Express an understanding of how their technology enhances shopper and advertiser experiences in e-commerce, tying in your interest in the Ads Growth team.

Discuss your project management skills and stress the importance of prioritizing tasks. Share specific aggressive timelines you've successfully met in the past, explaining how you coordinated with team members and stakeholders to ensure timely completion.

Frame your response around a specific instance where you led a technical meeting, explaining how you prepared for it, facilitated discussions, and resolved any conflicts. Your leadership style and how you ensure all voices are heard will be key points to highlight.

Share your strategies for keeping abreast of technology trends, such as following key journals, attending conferences, or participating in online forums. Emphasize your commitment to continuous learning and how it influences your software development practices.

Explain your testing practices, whether through unit tests, integration tests, or code reviews. Highlight the importance of writing clean, maintainable code to prevent issues down the line, providing examples of successful practices you've implemented.

Discuss the complexities involved in integrating user behavior data, managing large datasets, and ensuring high prediction accuracy. Provide insights on how you would foresee and mitigate potential pitfalls during development, showcasing your problem-solving skills.