Monetization Data Engineer Intern — Summer 2027

TikTok

San Jose, Northern (CA, KY)

Hybrid

USD 62,000 - 83,000

Part time

14 days+

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Benefits offered by this job

Health insurance

Life insurance

Wellbeing benefits

Paid holidays

Housing allowance

Job summary

TikTok is offering a Data Engineer Intern position in San Jose for Summer 2027. You will work with Product Managers, Data Scientists, and Engineers to build and optimize data pipelines and models powering monetization analytics.

This internship provides hands-on experience, mentorship, and exposure to big data tech. Applicants should be pursuing CS/Engineering; 12-week commitment; strong SQL and Python; internship benefits included.

Qualifications

Currently pursuing an Undergraduate/Master's in Computer Science, Engineering, or a related field.
Strong knowledge of SQL and experience working with relational and non-relational databases.
Proficiency in programming languages such as Python, Java, Go etc.
Solid understanding of data modeling and data warehousing concepts, data integration and ETL/ELT techniques.
Effective communication skills and ability to collaborate effectively with cross-functional teams.
Excellent problem-solving skills, attention to detail, and ability to thrive in a fast-paced environment.
Able to commit to working for 12 weeks during Summer 2027.

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.
Provide rapid response to SLA oncall support to business critical data pipelines.
Create and maintain good documentation for data assets and promote best practices for data governance within the data user community.