Data Engineer, PDPO - Offense & Defense

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.