Staff Data Privacy & DLM Platform Architect

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 209,000 - 438,000; Full time

Job summary

TikTok USDS Joint Venture LLC is seeking a Staff Software Engineer specialized in Data Privacy and Infrastructure to own the architecture of Data Lifecycle Management and PET integration. You will shape the long-term technical roadmap, ensure 100% visibility of data lineage, and lead cross-functional teams across data, security, and product engineering.

You will drive privacy-preserving technologies, scale governance across petabyte-scale data ecosystems, and mentor engineers while delivering

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science or a related field.
• 5+ years of professional software development in large-scale distributed systems.
• Experience with Hive, Spark, Kafka, and Kubernetes.

Responsibilities

• Define the architectural blueprint and long-term technical roadmap for the DLM Platform and PET integration.
• Lead design and scaling of high-throughput backend services managing data retention, archival, and purging.
• Architect self-service onboarding APIs and tools to onboard new apps into DLM with cost-aware efficiency.
• Define migration strategies for legacy systems into governance pipelines without impacting SLAs.
• Drive enterprise metadata and data lineage for real-time audits and compliance checks.
• Champion PETs and privacy-by-design across data platforms.

Skills

Distributed systems

Data governance

Technical leadership

Education

Bachelor’s, Master’s, or PhD in Computer Science or related field

Tools

Hive

Spark

Kafka

Kubernetes

Job description

TikTok USDS Joint Venture LLC is seeking a Staff Software Engineer specialized in Data Privacy and Infrastructure to own the architecture of Data Lifecycle Management and PET integration. You will shape the long-term technical roadmap, ensure 100% visibility of data lineage, and lead cross-functional teams across data, security, and product engineering.

You will drive privacy-preserving technologies, scale governance across petabyte-scale data ecosystems, and mentor engineers while delivering