Be ready to go over:

• List Comprehensions and One-Liners – Writing compact, efficient code to manipulate multi-dimensional arrays or lists.
• Object-Oriented Programming (OOP) – Building modular ETL pipelines using classes, inheritance, and polymorphism.
• Data Structures – Choosing the right collection types (dicts, sets, tuples) to optimize memory and execution time.
• Advanced concepts (less common) – Generator functions for streaming large files, custom decorators for logging and retrying pipeline steps, and concurrency modules.

Example questions or scenarios:

• "Write a single-line Python expression to initialize a 2D array of size N x M with sequential integers."
• "How would you design a base ETL class in Python that uses polymorphism to support reading from both S3 and local file systems?"

Systems Design & Practical Presentation

For senior roles or specific regional teams, you will face design challenges that test your ability to build complete, end-to-end data systems. This may include resolving a series of software tasks and presenting your architectural choices.

Be ready to go over:

• Pipeline Orchestration – Designing workflows that handle dependency management, retries, and failure alerts.
• Data Ingestion – Deciding between batch and real-time streaming architectures depending on business latency requirements.
• Presentation Skills Pitching your technical solutions clearly to a panel, explaining trade-offs, and justifying tool selection.

Example questions or scenarios:

• "Walk us through a project where you had to design a pipeline to process high-velocity telemetry data. What were the bottlenecks, and how did you resolve them?"
• "Present a solution to ingest daily reporting files, perform validation checks, and update a downstream dashboard with minimal latency."

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.