Data Warehouse Engineer Graduate (Data Platform, TikTok PGC) - 2027 Start

关于这个机会

Team Introduction The mission of the PGC Data BP team is to empower the PGC business through data. Our goal is to build data warehouses that support both batch and streaming data processing, as well as data products that deliver actionable insights through efficient metrics and dashboards. These capabilities enable smarter business decisions and support sustainable business growth. If you are looking for a challenging environment where you can push your limits and make meaningful impact, this is the team for you! We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Participate in building offline and real-time data warehouses for the TikTok PGC business. - Work with PB-scale data and support the daily processing of hundreds of billions of user data records. - Support the full big data lifecycle, including data generation, transmission, modeling, statistical analysis, experiment evaluation, and visualization. - Design and build scalable data flows, data warehouses, scheduling systems, query engines, data services, analytics systems, process standards, and data tools/products to lower the barrier to data usage, ensure stable and efficient system operations, and maximize data value.

任职要求

Minimum Qualification(s) - Individuals who are completing or have recently completed a Bachelor's / Master's degree in Computer Science, Software Engineering, or a related technical discipline. - Solid technical foundation with strong coding skills in SQL, Python, Scala, Java, or similar languages. Preferred Qualification(s) - Experience with big data tools and frameworks such as Spark, Hadoop, Hive, Flink, Kafka, and HBase. - Strong interest in big data technologies, with a self-motivated and proactive learning mindset.

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