• Participate in the design, development, and optimization of the company's big data platform to support continuous business growth and data-driven decision-making.

• Responsible for the setup, performance tuning, monitoring, and daily operations of the ClickHouse cluster, ensuring high availability and high performance of the system.

• Participate in the development, deployment, and maintenance of Flink streaming processing tasks to ensure the stable operation of real-time data processing links.

• Support the data service needs of the business by developing data API services based on Java Spring Boot.

• Assist the data science team in building data pipelines to support the training and online services of algorithm models.

• Continuously optimize data processing workflows and system architecture to enhance system stability and scalability.

• Take initiative in projects, drive problem-solving, demonstrate a sense of ownership, and maintain strong execution and communication skills under pressure.

• Bachelor's degree or above, with a preference for majors in Computer Science, Software Engineering, Information Technology, or related fields.

• 3 to 5 years of experience in big data.

• Solid foundation in databases: Familiarity with the principles of relational databases (such as MySQL, PostgreSQL) and columnar databases (such as ClickHouse, Doris), with an understanding of their underlying storage, query optimization, and other key mechanisms.

• Strong development capabilities: Proficient in Java and experienced in developing REST API services using the Spring Boot framework.

• Excellent communication and collaboration skills, able to work closely with data analysis, product, and business teams.

• Strong sense of responsibility, with good stress resistance and problem-solving abilities, capable of proactively driving work progress.

• Willing to relocate to Japan after six months (company visa support provided).

Bonus points if you also have:

1. Practical experience with components such as Kafka, Zookeeper, HDFS, Hive, and Airflow;

2. Project experience related to recommendation systems, user profiling, personalized ranking, etc.;

3. Background in predictive algorithms (such as time series forecasting, user behavior prediction);

4. Familiarity and practical experience with large language models (LLM, such as ChatGPT, LLama, etc.) in business or system application scenarios (such as data augmentation, automatic summarization, intelligent Q&A, etc.);

5. Experience participating in real-time data warehouse and indicator system construction projects;

6. Preference for candidates with experience building big data platforms from 0 to 1.

ClickHouse

• Proficient in ClickHouse data modeling, query optimization, and resource management;

• Practical experience in cluster operation and maintenance, troubleshooting, and performance monitoring;

• Familiar with the integration of ClickHouse with data middleware/stream processing/scheduling systems.

Flink

• Familiar with the underlying mechanisms of Flink, such as checkpointing, state backend, window mechanisms, etc.;

• Able to independently write complex Flink real-time processing tasks and resolve performance issues during execution;

• Experience in Flink cluster deployment and stability maintenance.