About the team:
The Privacy and Data Protection Office (PDPO) leads, supervises, and empowers all of TikTok s privacy work in an accountable and industry-leading way. The team is the in-house expert on the privacy risk landscape and partners across the company to implement the safeguards and technical mitigations that ensure users privacy is honored across TikTok s products and platforms.
The Offense and Defense team establishes capability to proactively identify, monitor, and mitigate privacy risks across target domains; build a scalable monitoring system as the second line of defense; translate risk objectives into detection capabilities to enhance visibility across key privacy risk areas; and strengthen the technical and data foundation to support reliable monitoring, investigation, and risk-informed decision-making across the organization.
Responsibilities
- Design, construct, test, and maintain robust, fault-tolerant, and scalable data pipelines and data services to support high-throughput analytical workloads.
- Build, optimize, and expand storage solutions, data models, and enterprise data warehouses using modern distributed databases and caching technologies.
- Investigate and integrate up-and-coming big data tools, open-source frameworks, and modern technologies into existing production environments.
- Implement fault-tolerant mechanisms, triage and debug complex data infrastructure issues, and establish operational monitoring to protect system reliability and SLA.
- Partner with data scientists, analysts, product managers, and software engineering teams to align data platform capabilities with core business goals and deliver seamless integrations with third-party data systems. Minimum Qualification(s)
- Must have 1 year of experience in each of the following:
- Designing and modeling data warehouses to power business intelligence, analytics, reporting, and data applications.
- Implementing production ETL workflows and data processing using Hive, Spark, Hadoop, and/or SQL Server to optimize execution performance and query latency.
- Developing production code using SQL, Python, and/or Java.
- Troubleshooting, triaging, and debugging complex distributed data infrastructure and pipeline failures.
- Building scalable data services or serving layers utilizing HBase, Elasticsearch, ClickHouse, and/or SQL Server.
Preferred Qualification(s)
- Strong analytical thinking with a track record of thriving in fast-paced, rapidly evolving environments and taking ownership of ambiguous technical problems.
- Excellent communication and cross-team execution skills in a fast-paced environment.