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Data Development Engineer - Global Payment - Singapore

单位:字节跳动类别:数据挖掘类型:社招地点:新加坡更新:2026-09-24

岗位信息

招聘单位字节跳动
工作地点新加坡
官方更新时间2025-10-14 09:52:26

职位描述

About Global Payment

The Global Payment team of ByteDance provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on to ensure that our users have a smooth and secure payment experience on ByteDance platforms including TikTok.

The Data Intelligence team in Global Payment leads the efforts of discovering data-driven business values for Global Payment, by collecting, visualising and mining generated data from the pipeline of whole Global Payment system. The outcomes include optimising the key business metrics, improving Global Payment products and user experiences, risk management through data intelligence, predicting the trends from historical data, etc.

Responsibilities:

1. Responsible for the data flow and related data service construction of ByteDance's global payment business;

2. Addressing ultra-large-scale data issues, processing hundreds of billions of incremental user data daily;

3. Responsible for the real-time transmission, cleaning, conversion, and calculation of streaming data, and providing efficient query services externally;

4. Participate in data governance work to improve data usability and quality;

5. Deeply understand and reasonably abstract business requirements, leverage data value, and cooperate closely with business teams.

任职要求

Minimum Qualifications:

- Bachelor degree or above in Computer Science, Statistics, Mathematics or other related majors;

- Familiar with Linux operating system and development environment;

- Possess solid computer fundamentals (data structures, operating systems, etc.);

- Proficient in any one programming language such as C/C++, Java, Python;

- Sensitive to data, meticulous and conscientious, with the ability to identify problems from data.

Preferred Qualifications:

- Experience in open-source project research or contribution;

- Participated in ACM or other software development competitions;

- Familiar with one or more of the big data processing tools/frameworks, including but not limited to: Hadoop, MapReduce, Hive, Storm, Spark, Druid, Kafka, HBase, Elasticsearch, etc.

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