Data Platform Intern: Big Data, ML & Search Innovation

TikTok Inc.; San Jose (CA); On-site; USD 22,000 - 33,000; Full time

Job summary

TikTok Inc. is offering an internship for a data engineer on the Data Platform E-Commerce team.

You’ll design and build data transformations, contribute to scalable big data systems, and gain hands-on experience across reporting and growth analysis. The program covers exposure to information retrieval, machine learning, NLP, and distributed systems, with a focus on applying theoretical knowledge to real-world challenges and building a solid foundation for a career in data engineering.

Qualifications

• Currently pursuing a Bachelor's degree in Computer Science or a related technical discipline.
• Able to commit to working for 12 weeks during Summer 2026.
• Experience in Big Data technologies (Hadoop, MapReduce, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, Flink, etc.).
• Experience with performing data analysis, data ingestion and data integration.

Responsibilities

• Design and build data transformations efficiently and reliably for reporting, growth analysis, and multi-dimensional analysis.
• Design and implement reliable, scalable, robust, and extensible big data systems supporting core products and business.
• Establish solid design and best engineering practices for engineers and non-technical people.

Skills

Data analysis

SQL queries

Education

Bachelor's degree in Computer Science or related technical discipline

Master's degree in Computer Science or related technical discipline

Tools

Hadoop

MapReduce

Hive

Spark

Metastore

Presto

Flume

Kafka

ClickHouse

Flink

Job description

TikTok Inc. is offering an internship for a data engineer on the Data Platform E-Commerce team.

You’ll design and build data transformations, contribute to scalable big data systems, and gain hands-on experience across reporting and growth analysis. The program covers exposure to information retrieval, machine learning, NLP, and distributed systems, with a focus on applying theoretical knowledge to real-world challenges and building a solid foundation for a career in data engineering.