Software Engineer Intern - Data Platform

San Francisco 22 months agoFull-time External
Negotiable
Work Mode: Onsite Responsibilities: Tencent Games Global Publishing Technology Team is the international unit of Tencent Games, a leading global platform for game development, publishing, and operation. Aiming to improve our games and transform the gaming industry, our mission is to solve the toughest challenges in gaming with technology. With offices in Palo Alto, Singapore, Shenzhen and around the world, our growth strategy is to build upon attracting the best talent and creating an amazing work atmosphere that balances the energy of a start-up with the resources of a global innovation leader. As the world’s leading technology company, we maintain an entrepreneurial spirit and an open mindset. If you are passionate about the gaming industry and eager to do groundbreaking work in a friendly, cross-cultural environment, we can provide unparalleled stability, resources, access to more than a billion players, and an international perspective. If you like us are ambitious and self-driven, we invite you to explore Tencent Games Global Publishing Center Tech Team and take challenges that will create new adventures for billions of players. Responsibilities: • Work with cross-functional teams and understand how data platform are developed and maintained at scale. • Build scalable data pipelines (using Spark, Airflow and Presto) to move data from different applications into our data warehouse. • Monitor and improve automated solutions to ensure quality and performance SLAs are met. • Maintain and support existing platforms and evolve to newer technology stacks and architectures Requirements: Qualifications • Currently pursuing a Bachelors or Masters degree in Computer Science, Data Engineering, or a related field. • Coding & scripting proficiency in languages such as Python, C++, Golang. • SQL knowledge in handling volumes of data and performance. Bonus • Passion in gaming. • Scratch-build a highly scalable, available, fault-tolerant data processing systems using cloud technologies, HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, and other big data technologies