Senior Software Engineer - Measurement - Data Engineering++

As a Senior Software Engineer - Measurement at LG Ad Solutions, your primary responsibilities include leading the design, development, and deployment of scalable ad measurement systems, collaborating with cross-functional teams for data accuracy, implementing AI and machine learning methodologies to assess the impact of advertisements, and optimizing the measurement infrastructure to ensure performance and reliability.

To qualify for the Senior Software Engineer - Measurement role at LG Ad Solutions, candidates should possess a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, along with 5+ years of experience in data engineering. Familiarity with programming languages such as Scala, Python, Go, C++, and JavaScript, along with a proven track record of working with large data sets, is essential.

Candidates for the Senior Software Engineer - Measurement role at LG Ad Solutions should be proficient in programming languages including Scala, Python, Go, C++, and JavaScript. These skills are critical for developing and implementing data-driven solutions in the ad measurement space.

At LG Ad Solutions, innovation is a core value, especially for the Senior Software Engineer - Measurement role. You will be empowered to drive technological advancements by integrating AI/ML into ad measurement systems and providing mentorship to junior engineers, fostering a culture where creativity and new ideas are encouraged.

As a Senior Software Engineer - Measurement at LG Ad Solutions, you can expect a collaborative team dynamic where you work closely with cross-functional groups, including data scientists, product managers, and other engineers. The team promotes open communication and supports innovation, making it an ideal environment for problem-solving and professional growth.

When answering this question, it's essential to highlight specific projects where you have applied AI/ML techniques to enhance data systems. Discuss the challenges you encountered and how your solutions improved performance or accuracy, emphasizing your understanding of machine learning principles.

Share concrete examples of how you identified inefficiencies in data handling processes and the solutions you implemented. Discuss best practices for data modeling, indexing, or partitioning and how these strategies led to better performance and scalability.

Discuss the processes you use to assess data quality such as validation techniques, consistency checks, and transformation procedures. Emphasize the importance of documentation and communication with other teams to align on data expectations.

Talk about scalability, reliability, and performance as core pillars in your approach to designing systems. Highlight your experience with distributed computing and strategies to manage data growth, ensuring you address the unique requirements of ad measurement.

Illustrate your prioritization process by discussing how you assess project timelines, stakeholder demands, and resource availability. Mention tools or frameworks you rely on to maintain focus and track progress effectively.

Share your systematic approach to troubleshooting, including log analysis, monitoring tools, and collaboration with team members. Discuss how you break down problems and the importance of documenting your findings for future reference.

Demonstrate your communication and conflict-resolution skills. Describe scenarios where you listened to diverse viewpoints and facilitated discussions to reach consensus, ultimately fostering collaboration and mutual respect.

Highlight a specific instance where you mentored a junior engineer or peer, outlining the learning objectives, the methodologies you used, and the outcomes of that mentorship. Emphasize the importance of fostering growth within the team.

Discuss your commitment to continuous learning through online courses, webinars, conferences, or participation in professional networks. Mention specific resources or communities you follow to keep your knowledge current.

Share your reasoning for favoring a particular programming language based on your experiences and the contexts in which it excels. Discuss practical applications and how it has helped you solve complex engineering problems effectively.