Site Reliability Engineer, Ads Data Platform- USDS

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. . Data Security ( USDS ) is a subsidiary of TikTok in the .

This new, security-first division was created to bring heightened focus and governance to our data protection policies and content assurance protocols to keep .

users safe. Our focus is on providing oversight and protection of the TikTok platform and . user data, so millions of Americans can continue turning to TikTok to learn something new, earn a living, express themselves creatively, or be entertained.

The teams within USDS that deliver on this commitment daily span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions and more.

Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.

Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity;

to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together.

That's how we drive impact - for ourselves, our company, and the communities we serve. Join us. Site Reliability Engineering (SRE) combines software and systems engineering to build and run large-scale, massively distributed services and infrastructures.

As a site reliability engineer in the Ads data platform area, you will have the opportunity to manage the services and infrastructures in one of the largest data plaforms in the world that directly supports the TikTok Ads ecosystem.

You'll need to ensure the data, services and infrastructures are reliable, fault-tolerant, efficiently scalable and cost-effective.

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager / department.

We regularly review our hybrid work model, and the specific requirements may change at any time. Responsibilities :

• Engage in and improve the whole lifecycle of service, from inception and design, through to deployment, operation and refinement
• Ensure reliable, fault-tolerant, efficiently scalable and cost-effective data, services and infrastructures
• Maintain production services by measuring and monitoring availability, latency and overall system health. Practice sustainable incident response and blameless postmortems.
• Establish best engineering practice for engineers and non-technical stakeholders
• Design and implement reliable, scalable, robust and extensible big data systems that support core products and business

Minimum Qualification : - Bachelor's degree in Computer Science, a related technical field involving software or systems engineering, or equivalent practical experience- Experience with algorithms and data structures- Solid communication and collaboration skills- Experience with Big Data technologies such as M / R, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink etc- Experience with Ads systems is a plus