Lead Data Engineer - Data Solutions

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 a Lead Data Engineer, you will be responsible for 0-to-1 build up both the team and the data pipeline. 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. Additionally, you will provide technical guidance, mentorship, and support to team members. 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. Build and lead a high-performing data engineering team with a clear strategy, providing business, technical, and personal development coaching; 4. 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; 5. Foster a collaborative and inclusive team culture within and across teams, collaborate with data scientists.

Minimum Qualifications : 1. Bachelor's or Master's degree in Computer Science, Engineering, or related field; 2. 3 years of experience in data engineering, with demonstrated expertise in building scalable data pipelines and infrastructure; 3. Proficiency in programming languages such as Python, SQL, and Java; 4. Experience with big data technologies such as Apache Spark, Hadoop, and Kafka. Preferred Qualifications : 1. Strong understanding of database systems, data warehousing, and distributed computing concepts; 2. Excellent leadership, communication, and interpersonal skills; 3. Proven track record of leading teams and delivering complex data engineering projects; 4. Ability to thrive in a fast-paced environment and manage multiple priorities effectively.