Data Engineer Graduate (Monetization Data) - 2027 Start

About the role

The Monetization Data team builds the data foundation that powers TikTok's global advertising and monetization products. We design and operate large-scale batch and real-time data pipelines, data warehouses, and analytics platforms that help improve advertiser experience, measure business performance, support experimentation, and drive product and strategy decisions. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines to process large-scale user behavior, advertising, and monetization data.
• Develop reliable data models, datasets, and metrics that support ads ranking, measurement, experimentation, business analytics, and strategic decision-making.
• Partner with product managers, data scientists, analysts, and engineering teams to understand data needs, define success metrics, and deliver actionable insights.
• Improve data quality, observability, latency, cost efficiency, and platform reliability across large-scale distributed systems.
• Contribute to the evolution of big data infrastructure and computing platforms, including Spark, Flink, Hive, Kafka, and related internal systems.

Requirements

• Individuals who are completing or have recently completed a Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Statistics, Mathematics or a related discipline.
• Strong programming skills in at least one general-purpose language such as Python, Java or Go.
• Strong SQL skills and understanding of relational databases, data modeling, or data warehousing concepts.
• Familiarity with distributed data processing or storage systems such as Spark, Flink, Hadoop, Hive, Kafka, Presto/Trino, or similar technologies.
• Strong problem-solving skills, data-driven thinking, and ability to use data to identify issues, form hypotheses, and validate solutions.
• Ability to work collaboratively in a fast-paced, cross-functional engineering environment.

Preferred Qualifications

• Internship, research, coursework, or project experience in data engineering, backend engineering, distributed systems, data analytics, or machine learning infrastructure.
• Experience building ETL/ELT pipelines, workflow orchestration, data quality checks, dashboards, or analytical datasets.
• Experience with advertising technology, recommendation systems, experimentation platforms, or user behavior data analysis.
• Familiarity with cloud data platforms, lakehouse architectures, or modern data tools such as Airflow, dbt, Iceberg, Delta Lake, Snowflake, BigQuery, Redshift, or Databricks.
• Experience using AI-assisted development tools, LLM applications, or agentic workflows to improve engineering productivity.
• Contributions to open-source projects, technical communities, hackathons, or substantial personal projects.

Pay

The base salary range for this position is $128,000 - $256,000 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work; this role may be eligible for additional discretionary bonuses/incentives and restricted stock units.

Benefits

• Day one access to medical, dental, and vision insurance.
• 401(k) savings plan with company match.
• Paid parental leave, short-term and long-term disability coverage, life insurance, and wellbeing benefits.
• 10 paid holidays per year, 10 paid sick days per year, and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).