[Publishing Platform Div.] Mid-level Data Engineer

KRAFTON is seeking a Mid-level Data Engineer to join their Publishing Platform Division in Seoul. This role is crucial in building and operating data platforms that support KRAFTON's publishing initiatives worldwide.

The position involves working with large-scale data systems, focusing on ETL processes and maintaining data quality in cloud environments. The successful candidate will be responsible for managing Hadoop-based platforms, developing new Spark-based solutions, and ensuring robust data monitoring systems are in place.

A unique aspect of this role is the collaboration with Chinese publishing partners, requiring strong technical expertise combined with Chinese language proficiency. The position is based in the Yeoksam area and involves participating in technical discussions with Chinese publishing companies and contractors.

Key technical requirements include extensive experience with Python and Scala for building data pipelines, proficiency in CI/CD practices, and expertise in data validation and monitoring systems. The ideal candidate will have at least 7 years of data engineering experience and a strong background in designing and operating technical architectures for large-scale data processing.

KRAFTON offers a comprehensive work environment where you'll be part of a team dedicated to pushing the boundaries of gaming enjoyment through technology. The company is known for its globally recognized production studios and commitment to creating uniquely enjoyable gaming experiences.

This role presents an excellent opportunity for a seasoned data engineer who wants to make an impact in the gaming industry while working with cutting-edge data technologies. The position offers exposure to international projects and the chance to work with a diverse team of passionate professionals.

Preferred qualifications include experience in the gaming industry or global companies, familiarity with cloud platforms (AWS, Google Cloud, Azure), and expertise in distributed processing systems like Spark and Map-Reduce. Knowledge of infrastructure management using Terraform and Kubernetes is also valued.