About The Team

The TikTok Data Ecosystem Team has the vital role of crafting and implementing a storage solution for offline data in TikTok's recommendation system, which caters to more than a billion users. Their primary objectives are to guarantee system reliability, uninterrupted service, and seamless performance. They aim to create a storage and computing infrastructure that can adapt to various data sources within the recommendation system, accommodating diverse storage needs. Their ultimate goal is to deliver efficient, affordable data storage with easy-to-use data management tools for the recommendation, search, and advertising functions.

What you will be doing:

1. Responsible for the design and development of distributed database Hbase-related components.
2. Responsible for the design and development of single-node LSM engine Rocksdb-related components.

Qualifications

Minimum Qualifications:
- Bachelor's Degree or above, majoring in Computer Science, or related fields,
- Proficiency in one of C/C++/Java;
- 2+ years of relevant development experience in storage engines resource management, system tuning, capacity planning (e.g., RocksDB, Redis)
- 2+ years experience in distributed systems and big data technology like Kafka and Hadoop

Preferred Qualifications:

• Embrace the use of open-source software, possess a track record of involvement in open-source projects, and demonstrate a keen enthusiasm for engaging with the latest and most advanced technologies.
• Exhibit knowledge in distributed consensus algorithms like Paxos/Raft.
• Show familiarity with distributed transaction models.
• Demonstrate proficiency in typical storage engines, including RocksDB, and have a deep understanding of the inner workings of Redis at the low-level code level.
• Display expertise in low-level aspects of operating systems, with a background in optimizing system performance for TCP/IP, I/O operations, and other critical component