Staff Back-end Engineer - Ads Measurement

The Staff Back-end Engineer - Ads Measurement at Coupang plays a crucial role in designing and building large-scale data processing systems that support the Ads business. This includes leading the technical direction for the team, understanding Ads business logic, and translating it into efficient data models. Additionally, the engineer will contribute to developing a robust data processing platform, ensuring it meets the demands of a rapidly growing Ads infrastructure.

To be considered for the Staff Back-end Engineer - Ads Measurement role at Coupang, candidates must possess a Bachelor’s degree in Computer Science, Computer Engineering, or a related field, along with at least 6 years of experience working with algorithms, system design, and large distributed systems. Proficiency in programming languages like C++, Java, or Scala is essential, along with strong communication skills and experience working in cross-functional teams.

In the role of Staff Back-end Engineer - Ads Measurement, you'll work with a variety of technologies and tools designed to optimize and enhance large-scale data processing systems. Key technologies include AWS for cloud services, as well as frameworks like Spark, HBase, Hive, and Kafka. Familiarity with advertising systems, search indexing, and various types of digital advertising will also be beneficial.

Coupang fosters a supportive and multicultural team environment where collaboration and innovation thrive. As a Staff Back-end Engineer - Ads Measurement, you’ll be part of a fast-paced, team-oriented culture that encourages diverse perspectives and proactive problem-solving. This dynamic setting provides engineers with the opportunity to take ownership of projects while working alongside other talented professionals.

Coupang offers exciting career growth opportunities for the Staff Back-end Engineer - Ads Measurement role. With the continuous expansion of our Ads business, engineers can advance their careers by leading innovative projects, exploring emerging technologies, and enhancing their skill sets. The supportive environment encourages personal and professional development, paving the way for leadership roles in the future.

When answering this question, highlight specific projects you've worked on that involved designing and implementing large-scale data processing systems. Discuss the technologies you used, the challenges faced, and how you overcame them. Emphasize your ability to scale systems efficiently while maintaining performance.

Be honest about your proficiency in C++, Java, Scala, or any other relevant programming languages. Discuss why you enjoy using a particular language, focusing on aspects like performance, ease of use, or library support. Consider relating this to specific projects where these languages were a pivotal part of the success.

Choose a relevant technical challenge from your past experiences that demonstrates your analytical and problem-solving skills. Detail the situation, your approach to finding a solution, and the impact of your resolution on the project or team.

Discuss strategies you’ve employed to ensure system availability and scalability, such as load balancing, redundancy, and failover techniques. Offer examples that illustrate how you've applied these strategies in real projects.

Show your knowledge of how data processing is integral to the Ads business model by explaining concepts like user targeting, attribution, and performance measurement. Relate this understanding to your experience and how it affects the systems you've built.

Explain your methods for staying informed, such as following relevant blogs, participating in communities, or attending conferences. Mention specific resources or technologies that have recently influenced your work and how you apply new knowledge.

Outline your leadership style and approach to managing projects. Discuss how you coordinated with team members, set goals, and ensured project milestones were met. Highlight the project's outcome and what you learned as a leader.

Discuss specific monitoring tools you've used, such as APM (Application Performance Management) tools, and how these tools helped you gain insights into system performance. Talk about any optimizations you made based on this data.

Explain your systematic approach toward identifying and fixing issues in a multi-threaded context. Discuss techniques such as logging, stepping through code, or utilizing debuggers as well as the importance of testing under various conditions.

Share your insights on successful collaboration, emphasizing the importance of clear communication, mutual respect, and understanding different roles within a project. Provide examples of how you've applied these principles in past team interactions.