Job Description

The Ads Data Team builds and manages the petabyte-scale data infrastructure, batch/realtime pipelines and services to support Tiktok's global Ads business. We are committed to building a robust data foundation and scalable data applications, unblocking the full potential of advertising data to optimize advertiser experience, boost business growth, empower strategy execution.

We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok.

Internships at TikTok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks beginning in 2026 .

Candidates can apply to a maximum of two positions and will be considered for jobs in the order your apply. The application limits is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible. Please state your availability clearly in your resume (Start date, End date).

Summer Start Dates:

May 11th, 2026

May 18th, 2026

May 26th, 2026

June 8th, 2026

June 22nd, 2026

Key Responsibilities:

1. 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.

2. Evaluate, implement and maintain data infrastructure tools and technologies to support efficient data processing, storage and query.

3. Design, build and optimize scalable data pipelines to ingest, process and transform large volumes of data.

4. Design and implement robust data models and visualization to support complex analytical queries and reporting requirements.

5. Ensure the data integrity, accuracy and consistency of data by implementing data quality checks, validation processes and monitoring mechanisms.

6. Continously optimize data pipelines, queries and processes to improve performance, reduce latency and enhance scalability.

7. Provide rapid response to SLA oncall support to business critical data pipelines.

8. Create and maintain good documentation for data assets and promote best practices for data governance within the data user community.