Staff Data Engineer

Responsibilities

• Develop and implement advanced data solutions supporting billing, reporting, and other core systems.
• Design and maintain scalable, optimized data pipelines for efficient collection, processing, and storage.
• Collaborate with data scientists, product managers, and engineers to refine and improve data processes.
• Translate complex business requirements into robust technical solutions.
• Conduct A/B testing and performance analysis to validate and iterate on data processes.
• Stay current with industry trends and emerging technologies in data engineering and ad tech.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• 8+ years of related experience (or 6 years with a Master's, or 3 years with a PhD).
• Proven experience delivering data engineering solutions within the ad tech industry.
• Proficiency in Python, Java, and Scala.
• Experience with Kubernetes and stream processing frameworks such as Flink or Apache Ignite.
• Expertise in big data technologies including Hadoop, Spark, SQL, and MapReduce.
• Hands-on experience with orchestration tools like Airflow.
• Solid understanding of statistical concepts and problem-solving skills.

Preferred Qualifications

• Experience with RESTful APIs and Golang.
• Familiarity with real-time data processing and streaming technologies.
• Knowledge of end-to-end digital advertising ecosystems and industry standards.
• Experience with Snowflake and related cloud data technologies.

Benefits

• Medical, Dental, and Vision insurance.
• 401(k) and Life Insurance.
• Employee Purchase Program and Tuition Assistance.
• Paid Time Off and Wellness Incentives.
• Student Loan Program.

About the Company

Samsung Ads is a leading innovator in advertising technology, dedicated to providing cutting-edge solutions that optimize ad performance and deliver exceptional results for clients. As part of Samsung Electronics, we leverage global scale and relentless innovation to transform the digital advertising landscape.