Data Engineer - Trust & Safety - San Jose

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 and 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.
We are looking for passionate Data Engineers that have strong problem solving skills to join forces with talented cross functional partners (business operation, data science, engineering and product management) to solve some cutting-edge challenges in big data and Al industry, which requires strong passion and capability of innovation. In this role, you will contribute to the company's core business across innovative advertising products, campaign management and measurement solutions. You will see a direct impact from your day-to-day work to customer satisfaction and company growth.

Responsibilities:
- Work closely with Product Managers, Data Scientists/Analysts, and Software/Machine Learning Engineers and other stakeholders to understand data requirements and deliver data solutions that meet business needs.
- Evaluate, implement and maintain data infrastructure tools and technologies to support efficient data processing, storage and query.
- Design, build and optimize scalable data pipelines to ingest, process and transform large volumes of data.
- Design and implement robust data models and visualization to support complex analytical queries and reporting requirements.
- Ensure the data integrity, accuracy and consistency of data by implementing data quality checks, validation processes and monitoring mechanisms.
- Continuously optimize data pipelines, queries and processes to improve performance, reduce latency and enhance scalability.
- Create and maintain good documentation for data assets and promote best practices for data governance within the data user community