Site Reliability Engineer, Data Platform-TikTok-US-Tech Services

Seattle, Washington, United States

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TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul and Tokyo.

Why Join Us
At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.

Team Introduction
Tiktok's Data Platform Team focuses on challenges in the areas of data infrastructure and data products. The team is in charge of various aspects including Query Engine, Logging and Data Ingestion Infra, Experimentation Platform, as well as Workflow Management Platform. The goal is to support ad-hoc/interactive queries, batch pipelines, logging and ingesting large amounts of realtime data, and supporting A/B testing for all product features launches.

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 data platform area, you will have the opportunity to manage the services and infrastructures in one of the largest data platforms in the world. You'll need to ensure the data, services and infrastructures are reliable, fault-tolerant, efficiently scalable and cost-effective. You'll also have the opportunity to design, build and deliver all kinds of systems as a software engineer.

• 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 services once they are live by measuring and monitoring availability, latency and overall system health. Practice sustainable incident response and blameless postmortems.
• Establish best engineering practice for engineers as well as non-technical people
• Design and implement reliable, scalable, robust and extensible big data systems that support core products and business
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: A/B testing Big Data Engineering Pipelines Testing

Region: North America
Country: United States

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