Data Platform Tech Lead & Manager — AI-Driven Reliability

TikTok USDS Joint Venture

San Jose (CA)

On-site

USD 209,000 - 438,000

Full time

4 days ago

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Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Parental leave

Short-term and long-term disability

Life insurance

Wellbeing benefits

Holiday, sick days and paid personal/s

Paid Personal Time

Job summary

TikTok USDS Joint Venture is seeking a Tech Lead Manager for the Data Platform team to guide data engineers and software engineers in delivering scalable data assets on time. You will own end-to-end reliability, collaborate with Product, Analytics, and Data Science partners, and drive integration of AI-powered self-healing and governance across data pipelines.

You will work with the Data Foundation team to shape platform capabilities, improve throughput and cost efficiency, and ensure governance

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
5+ years of experience building and operating enterprise-grade data platforms or large-scale distributed data systems, including 3+ years in an engineering leadership or engineering management role overseeing technical teams in a cross-functional, fast-paced environment.
Hands-on experience operating production batch and streaming systems built on technologies such as Spark, Flink, Hadoop, Kafka, Druid, ClickHouse, or equivalents — including on-call ownership, SLA management, and incident response. Must have a builder mindset.
Strong grasp of modern data architectures (data lakes, data warehouses, lakehouse patterns) and of what makes large-scale pipelines reliable, efficient, and observable.
Demonstrated ability to improve throughput, reliability, or cost efficiency of a data system without linear headcount growth — through automation, tooling, or architectural change.
Excellent communication, stakeholder management, and cross-functional partnership skills.
Ability to balance strategic thinking with hands-on problem-solving.

Responsibilities

Lead and grow the team: Manage, coach, and develop a team of data engineers. Foster ownership, operational excellence, engineering rigor, and a builder's mindset toward automation and AI.
Own operational delivery for your business line: End-to-end accountability for reliability, timeliness, and quality of pipelines, jobs, and data assets; own SLAs, on-call health, incident response, and postmortem-driven improvement.
Innovate with software, automation, and AI: Build or adopt tooling for AI-assisted SRE, self-healing pipelines, LLM-powered data development and code review, automated data quality and governance checks, and cost optimization.
Partner with the business: Be the primary engineering point of contact for Product, Analytics, Data Science, and Engineering; translate priorities into a concrete data delivery and reliability roadmap.
Collaborate with the Data Foundation team: Co-shape data platform requirements, adopt new capabilities, bring foundation capabilities to business, and reflect business realities.
Uphold governance and compliance: Ensure pipelines, datasets, and tooling meet data governance, privacy, security, and regulatory requirements in the US data environment.