Data Platform Engineering Manager - AI-Driven Reliability

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) match

Parental leave

Disability insurance

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid personal time

Job summary

TikTok USDS Joint Venture LLC is seeking an Engineering Manager for the Data Platform team. You will lead data and software engineers, delivering large-scale data assets reliably and on time across multiple data centers.

You will drive AI-assisted reliability, self-healing pipelines, and cost optimization, while partnering with Product, Analytics, and Data Science to align roadmaps with business needs.

Qualifications

• 5+ years building and operating enterprise-grade data platforms.
• 3+ years in engineering leadership overseeing technical teams.
• Hands-on experience with Spark, Flink, Hadoop, Kafka, Druid or ClickHouse.
• Strong understanding of data lakes, warehouses, and lakehouse patterns.
• Proven ability to improve throughput, reliability, or cost efficiency.
• Excellent communication and cross-functional partnership skills.

Responsibilities

• Lead and grow the team of data engineers and software engineers.
• Own end-to-end delivery for batch and streaming pipelines and data assets.
• Drive AI-assisted reliability, self-healing pipelines, and automated governance.
• Collaborate with Product, Analytics, Data Science, and Engineering partners.
• Co-shape data platform requirements with the Data Foundation team.
• Ensure governance, privacy, security, and regulatory compliance.

Skills

Communication

Stakeholder management

Cross-functional collaboration

Leadership

Education

Bachelor's or Master's in CS/Engineering

Tools

Spark

Flink

Hadoop

Kafka

Druid

ClickHouse

Job description

TikTok USDS Joint Venture LLC is seeking an Engineering Manager for the Data Platform team. You will lead data and software engineers, delivering large-scale data assets reliably and on time across multiple data centers.

You will drive AI-assisted reliability, self-healing pipelines, and cost optimization, while partnering with Product, Analytics, and Data Science to align roadmaps with business needs.