Staff Security Engineer - Data Security Engineering

6w1 month ago

Coupang

Seoul, KR · Contract

About this role

Coupang exists to delight customers and fulfill its mission when shoppers say they could not live without the service. The company drives innovation across the commerce industry through relentless focus on convenience in shopping, dining, and daily life.

Coupang combines startup agility with the scale of a global public company. Employees receive opportunities to act with entrepreneurial spirit, launch new initiatives, and expand the business while maintaining rapid growth and continuous service launches.

Every team member is committed to building the future of commerce. Engineers solve customer problems, challenge conventional limits, and deliver high-availability systems using cutting-edge technology in a hyper-connected environment.

Staff Security Engineers collaborate across engineering, data, privacy, and compliance groups to embed controls into large-scale data platforms and reduce sensitive data exposure risks through automation and governance.

Requirements

Deep experience in data security or security engineering.
Hands-on experience with PII detection, data classification, data masking, and access control.
Experience with large-scale data platforms including S3, Hive, Redshift, RDS, MySQL, PostgreSQL, Kafka, MongoDB, DynamoDB, and Elasticsearch.
Experience with data lineage, data flow mapping, data governance, or metadata management.
Proficiency in Python, Bash, Java, or similar programming and scripting languages.
Experience developing internal tools, automation workflows, APIs, or security platforms.
Understanding of cloud security, especially AWS data services and IAM-based access control.
Strong collaboration skills across engineering, data, compliance, privacy, and business teams with ability to translate complex risks into technical solutions.

Responsibilities

Lead design and implementation of data security programs for enterprise-wide identification, classification, protection, and monitoring of sensitive data.
Build systems that leverage AI and automation to analyze PII detection results, improve accuracy, reduce false positives, and enable rapid response.
Design and develop internal security tools and platforms supporting data scanning, PII review, access control governance, and risk management.
Partner with engineering, data platform, privacy, compliance, and business teams to identify sensitive data risks and define response plans.
Integrate sensitive data controls into data pipelines, lakes, warehouses, and operational systems in collaboration with data owners and platform teams.
Support data lineage analysis to map collection, storage, transformation, sharing, and usage flows of sensitive data across systems.
Define technical requirements for data detection, classification, masking, tokenization, access control, and audit logging solutions.
Drive remediation of sensitive data exposure risks including unnecessary PII storage, plaintext data, excessive access rights, and unsafe data movement.