Data Security Engineer - Global Monetization

We are the Global Monetization Product and Technology Security BP team. We partner closely with product, engineering and operations to safeguard Global Monetization Product and Technology across regions. Our scope covers application security, data security, privacy compliance and architecture security. We build and operate the SDLC/DevSecOps security program, conduct threat modeling, code reviews, penetration testing, red/blue exercises and vulnerability management, respond to security incidents rapidly and drive systemic fixes. We value pragmatism, ownership and cross-team collaboration, protecting business growth and user trust at global scale. Responsibilities - Design and implement data security products and capabilities covering data classification, data asset mapping, data lineage tracking, encryption, data sharing, access management, security auditing and security baselines. - Identify and assess data security risks, develop remediation plans, coordinate implementation and follow up to verify that risks are addressed. - Continuously evaluate the effectiveness of data security controls and support incident detection, response, investigation and evidence collection. Minimum Qualifications - Bachelor’s degree or above in Information Security, Network Security, Computer Science or a related technical field. - Familiarity with the data security lifecycle, understanding of data security risk points and key development tasks within each lifecycle, and experience in building data security systems. - Familiarity with common security attack and defense techniques and closed-loop risk management approaches, with practical experience in data security risk identification and governance, and a strong understanding of data sensitivity. - Familiarity with data security products, such as data leakage prevention, UEBA, data discovery and classification, data encryption and decryption, and data sharing, with experience in data security product planning, design, development and operational implementation. - Familiarity with enterprise-level big data security issues, such as Hadoop, HDFS and Elasticsearch. - Logical thinking, communication and coordination skills, and project management skills. Preferred Qualification(s) - Practical experience using data mining, data analysis or threat intelligence analysis for information security.