Data Engineer – Data Solutions

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok’s global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Creation 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.

About the team
The success of TikTok’s data business model hinges on the supply of a large volume of high quality labeled data that will grow exponentially as our business scales up. However, the current cost of data labeling is excessively high. The Data Solutions team is built to understand data strategically at scale for all Global Business Solution (GBS) business needs. Data Solutions Team uses quantitative and qualitative data to guide and uncover insights, turning our findings into real products to power exponential growth. Data Solutions Team responsibility includes infrastructure construction, recognition capabilities management, global labeling delivery management.

About the role
As Data Engineer, you will be working on cutting-edge challenges in the big data and AI industry which requires strong passion and capability of innovation. You will collaborate closely with cross-functional teams to understand business requirements and translate them into technical solutions.

Responsibility
1. Architect efficient, scalable and reliable data pipelines and infrastructure for ingesting, processing, and transforming large volumes of data;
2. Define the technical strategy and roadmap for data engineering projects in alignment with business objectives, actively evaluate and bring in industry best practices and state-of-the-art technical approaches, and timely update the strategy according to the rapid change of the industry;
3. Own and drive data engineering projects by leveraging both internal and cross-functional resources, setting meaningful and challenging targets, and achieving them with innovative approaches;