CJ ENM Mnet Plus Data Engineer Posting (Wanted 369830)

# CJ ENM Mnet Plus Data Engineer Posting (Wanted 369830)

AI Summary

Purpose:

• Preserve the supplied CJ ENM Mnet Plus Data Engineer posting as the binding input for a tailored resume and portfolio package.

Key points:

• Role: [Mnet Plus] Data Engineer, Seoul Mapo, 3-8 years, rolling recruitment.
• Core work: real-time and batch ETL/ELT, large-scale data processing and storage, data integrity and monitoring, and analyst/service-team collaboration on data marts.
• Hard requirements explicitly name Kafka streaming, PB/TB-scale distributed storage, one of Java/Scala/Python/Go, cloud data-lake operation, and SQL/RDBMS/NoSQL depth.
• Verified candidate strengths align with batch pipelines, Python/Go, TB-scale MySQL, data-quality checks, and monitoring; Kafka production streaming and S3-based data-lake operation remain explicit gaps.

Relevant when:

• Building or reviewing the CJ ENM Mnet Plus application package.
• Checking whether a resume claim is a direct match, transferable evidence, or a gap.

Do not read full document unless:

• Exact posting wording or the source/capture metadata is required.

Linked documents:

• ../../../skills/tailor-resume-to-job/SKILL.md
• ../../wiki/people/hyunwook.md
• ../../wiki/people/career-timeline.md

Open Questions

• The posting shows rolling recruitment, so there is no fixed closing date.
• No preferred-qualification section was visible in the captured page.
• The page did not expose a separate application-process or submission-constraint section.

Details

Source metadata

• Source: https://www.wanted.co.kr/wd/369830
• Supplied by the user: 2026-07-23
• Captured: 2026-07-23 21:12 KST
• Company: CJ ENM
• Team/product: Mnet Plus Data team
• Role: Data Engineer
• Location: CJ ENM Center, Sangam, Mapo, Seoul
• Experience range: 3-8 years
• Deadline: Rolling recruitment (상시채용)

Team context

The posting describes a combined Data Engineer and Data Analyst team that owns the lifecycle from collecting and loading global app/web traffic through analysis used for service, content, and business decisions. Current company context is separate from the job requirements: CJ ENM reported in March 2026 that Mnet Plus was approaching 45 million cumulative members and that average MAU had more than doubled year over year.

Company-context source:

• https://www.cjenm.com/ko/news/%EA%B8%80%EB%A1%9C%EB%B2%8C-genz%EA%B0%80-%EC%97%A0%EB%84%B7%ED%94%8C%EB%9F%AC%EC%8A%A4mnet-plus%EC%97%90-%EB%B9%A0%EC%A7%84-%EC%9D%B4%EC%9C%A0-%EC%BD%98%ED%85%90%EC%B8%A0-%EC%A1%B0%ED%9A%8C%EC%88%98-%EC%A0%84%EB%85%84-%EB%8C%80%EB%B9%84-6%EB%B0%B0-%EC%9D%B4%EC%83%81-%EC%A6%9D%EA%B0%80-%EB%9D%BC%EC%9D%B4%EB%B8%8C-%EC%8B%9C%EC%B2%AD%EB%8F%84-4%EB%B0%B0-%EC%9D%B4%EC%83%81-%EA%B8%80%EB%A1%9C%EB%B2%8C-%EB%82%A8%EC%84%B1-1020-%EC%8B%A0%EA%B7%9C-%EA%B0%80%EC%9E%85-%EC%95%BD-32-%EA%B8%B0%EB%A1%9D/

Captured posting requirements

Responsibilities:

• Design, develop, and operate large-scale real-time/batch ETL/ELT pipelines using Apache Kafka and related technology.
• Clean and process large-scale data and manage distributed storage such as a Data Lake or Data Warehouse.
• Guarantee data integrity and build pipeline monitoring.
• Collaborate with analysts and service developers to build data marts and improve data access.

Required qualifications:

• At least three years of data-engineering experience or equivalent capability.
• Experience building and operating real-time streaming pipelines with Apache Kafka.
• Experience reliably processing, distributing, and storing PB/TB-scale data.
• Proficiency in at least one of Java, Scala, Python, or Go, with Clean Code practices.
• Experience operating large-scale, data-lake-based pipelines such as S3 in AWS or GCP.
• Deep understanding of SQL, RDBMS such as BigQuery or Snowflake, and NoSQL databases.

Evidence boundary fixed at capture time

• Direct evidence: data-engineering tenure since 2021.06, Python and Go, Apache Airflow and Kubernetes batch operations, SQL/MySQL, 2.6 TB relational database work, data reconciliation, and monitoring.
• Transferable but not direct: batch-oriented file CDC and TB-scale relational storage do not satisfy Kafka streaming or distributed data-lake production experience.
• Explicit gaps: Kafka production streaming, PB-scale distributed processing, S3/GCP data-lake operation, BigQuery/Snowflake production use, and verified NoSQL production depth.