About the team PDPO(Privacy and Data Protection Office) is the organization to lead, supervise, and empower all TikTok's privacy work in an accountable and industry leading way. This team is the expert in the landscape of privacy risks and passionate about consulting across the company on implementing the proper safeguards and technical mitigations to ensure that our users’ privacy is honored across the TikTok's products and platforms. About the role We are seeking an experienced Data Engineer to join the Risk and Governance organization within PDPO to utilize big data techniques in building solutions to help envision TikTok's privacy evolution. You will be expected to conduct rigorous data investigations, develop scalable data solutions and build deep domain knowledge in privacy and data protection from your day by day work. -Develop data integrations via APIs to ensure seamless and reliable data ingestion. -Collaborate with the team to explore the integration of LLMs and agent-based systems into data workflows. - Design and build systematic data solutions and standardized data runbooks to improve efficiency and ensure accuracy for incident and inquiry response. - Sort out data inventories across the whole company in different formats and platforms to develop scalable monitoring systems that detect Privacy Risks and establish automated alerts. - Develop data pipelines to automate metrics reporting, drive metrics to improve Operational Excellence. - Conduct data investigation, data mining to find root causes, patterns and trends for privacy risks, and develop improvement or remediation plans for data protection. - Establish solid design and best engineering practice for data access controls and management - Collaborate with various XFN teams within the PDPO department and across organizations (. legal, security, engineering and product) to drive various projects on privacy and data protection.

Minimum Qualifications: - BS or MS degree in Computer Science, Engineering, Analytics, mathematics or related technical field or equivalent practical experience - Hands-on experience and deep understanding of various Big Data technologies (Hadoop, M/R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink - Proficient in SQL, Python, Schema design, ETL (Extraction, Transformation & Loading) - Experience with data visualization tools or platforms (. Dashboards, Tableau, - Strong communication and project management skills. Be comfortable working with a large number of XFNs to lead and drive projects at different stages. Preferred Qualifications: - Experience and knowledge on data privacy & data security is a plus - Passionate and self-motivated about big data and data privacy.