Samsung Ads Data Engineer interview questions & guide 2026

To help you prepare effectively, we have categorized representative questions based on real interview experiences at Samsung Ads. These questions highlight the core technical and programmatic concepts you are likely to encounter.

SQL & Data Manipulation

These questions assess your ability to extract, clean, and aggregate large datasets efficiently.

• Write a SQL query using complex joins and aggregate functions to calculate user retention metrics.
• How do you optimize a query that is running slowly due to large table scans and data skew?

Preparing for an interview at Samsung Ads requires a balanced approach. You must demonstrate both deep technical competence and the ability to explain your design decisions clearly. Your interviewers will look for practical problem-solving skills rather than rote memorization.

Role-related knowledge – You must show a deep understanding of data warehousing concepts, ETL/ELT pipelines, and distributed computing. Be ready to explain the trade-offs of different database engines and storage formats when operating at scale.

Problem-solving ability – Interviewers want to see how you dissect ambiguous problems. When given a complex data scenario, walk through your assumptions, structure your approach logically, and explain how you would scale the solution.

Communication & Presentation – In some regions, you may be asked to present a solution pitch to the team. You must be able to translate technical architectures into clear business value and defend your design choices under questioning.

The interview process at Samsung Ads is structured to evaluate your technical capabilities, architectural thinking, and team fit. While the exact steps can vary slightly depending on the office location and seniority of the role, the overall flow remains consistent.

The journey typically begins with an initial resume screening, followed by a screening interview or technical test conducted via Webex or a similar platform. This initial phase focuses on verifying your fundamental coding and SQL skills. Following a successful screen, you will move into the core technical rounds. These rounds dive deep into Python, SQL, big data system design, and your specific project experience. Some locations also incorporate a practical case study or software task presentation, where you solve a set of problems and pitch your solutions directly to the engineering team.

The final stages involve managerial and behavioral rounds. Here, the focus shifts to your roles and responsibilities in previous jobs, your collaboration style, and how your career goals align with the engineering culture at Samsung Ads.

The timeline above outlines the typical progression from the initial HR touchpoint to the final decision. Candidates should expect the entire process to take between three to six weeks, depending on team availability and local scheduling requirements. Use this timeline to pace your preparation, ensuring your coding fundamentals are sharp for the early stages and your system design and presentation skills are polished for the later rounds.

To excel at Samsung Ads, you need to understand the specific domains where candidates are evaluated most rigorously.

SQL and Data Architecture

SQL is a non-negotiable skill for any Data Engineer at Samsung Ads. You will be evaluated on your ability to write clean, performant queries that run over billions of rows of smart TV telemetry data.

Be ready to go over:

• Joins and Aggregations – Deep understanding of how join algorithms work and how to aggregate data over sliding time windows.

As a Data Engineer at Samsung Ads, your day-to-day work will be dynamic and highly collaborative. You will be responsible for the following core activities:

• Pipeline Development – Design, develop, and maintain robust, scalable batch and real-time data pipelines that process petabytes of Smart TV telemetry and advertising data.
• System Optimization – Monitor, troubleshoot, and optimize existing data workflows to improve performance, reduce execution costs, and guarantee data delivery SLAs.
• Cross-Functional Collaboration – Work closely with data scientists to implement machine learning models in production pipelines, and assist product managers in defining data schemas that capture new product features.
• Data Quality and Governance – Implement rigorous validation checks, automated testing, and monitoring to ensure the accuracy, completeness, and security of all downstream datasets.
• Platform Modernization – Evaluate and integrate emerging big data technologies and cloud services to continually improve the capabilities and efficiency of our data platform.

We look for candidates who possess a strong foundation in computer science and practical experience managing large-scale data infrastructures.

• Must-have skills – Proficient in Python (including OOP concepts) and highly skilled in writing complex, optimized SQL queries. Experience with big data frameworks (such as Apache Spark, Hadoop, or Hive) and cloud-based data warehouses (such as Snowflake, Redshift, or BigQuery).
• Nice-to-have skills – Experience in the AdTech domain, familiarity with real-time streaming tools (like Apache Kafka or Flink), and knowledge of orchestration platforms like Apache Airflow.
• Experience level – Typically requires a minimum of 3 years of hands-on data engineering experience, with a proven track record of designing and deploying production-grade pipelines.
• Soft skills – Strong analytical problem-solving abilities, excellent communication skills to articulate technical designs to non-technical stakeholders, and a collaborative mindset to work effectively in cross-functional teams.

Q: How technical is the Python coding portion of the interview? A: The coding questions generally focus on practical data manipulation, scripting efficiency, and basic algorithm design. You should be comfortable writing list comprehensions, using built-in data structures efficiently, and applying core OOP principles like polymorphism.

Q: Do I need prior experience in the advertising technology (AdTech) industry? A: While prior AdTech experience is a plus, it is not required. The team values strong core data engineering skills, system design capabilities, and the ability to learn complex domains quickly over specific industry background.

Q: What is the typical timeline for the interview process? A: The process generally takes between three to six weeks from the initial resume submission to the final decision. This timeline can vary depending on the specific team, location, and whether onsite presentation panels are required.

Q: Are there practical software or Excel tasks in the interview? A: In certain regions and specific team tracks, candidates may be given a set of practical tasks involving software tools (such as databases or Excel) to evaluate their hands-on data manipulation skills, followed by a presentation of their solutions.

• Master your past projects: Be prepared to discuss your previous projects in deep technical detail. You should clearly explain your specific contributions, the architectural choices you made, and the measurable business impact of your work.
• Optimize for readability: When writing code during the interview, focus on writing clean, readable, and modular code. Explain your thought process out loud as you write, especially when optimizing loops or structuring classes.
• Understand the scale: Remember that Samsung Ads operates at a massive scale. Whenever you design a system or write a query, proactively discuss how your solution will scale when processing billions of daily events.
• Prepare for the presentation: If your process includes a solution pitch or presentation, practice delivering your slides or explanation clearly. Focus on explaining why you chose a specific design over alternatives.

Joining Samsung Ads as a Data Engineer means working at the absolute forefront of the smart TV and digital advertising landscape. The pipelines you build and maintain will directly power high-impact business decisions and shape the future of TV advertising. It is a highly rewarding role that offers the opportunity to solve complex, petabyte-scale data challenges alongside a talented engineering team.

To maximize your chances of success, focus your preparation on solidifying your SQL optimization techniques, mastering Python's data-handling capabilities, and practicing your system design communication. Clear, structured thinking and a strong foundational grasp of data structures will set you apart.

You can explore additional interview insights, detailed company reviews, and comprehensive preparation resources on Dataford to ensure you are fully prepared for every step of the process.

The salary data above provides a representative range for the Data Engineer position at Samsung Ads. When evaluating an offer, consider that total compensation packages typically include a competitive base salary, performance-based bonuses, and comprehensive benefits. Your specific offer will depend on your experience level, technical performance during the interviews, and the geographic location of the role.