The posting
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
Job highlights
Career growth opportunity, Paid leave, Flat organization
Responsibilities
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. Design and implement an offline/real-time data architecture for large-scale recommendation systems.
2. Design and implement a flexible, scalable, stable, and high-performance storage system and computation model.
3. Troubleshoot production systems, and design and implement necessary mechanisms and tools to ensure the overall stability of production systems.
4. Build industry-leading distributed systems such as offline and online storage, batch, and stream processing frameworks, providing reliable infrastructure for massive data and large-scale business systems.
Qualifications
Minimum Qualifications:
- Bachelor's Degree or above, majoring in Computer Science, or related fields, with 1+ years of experience building scalable systems;
- Proficiency in common big data processing systems like Spark/Flink at the source code level is required, with a preference for experience in customizing or extending these systems;
- A deep understanding of the source code of at least one data lake technology, such as Hudi, Iceberg, or DeltaLake, is highly valuable and should be prominently showcased in your resume, especially if you have practical implementation or customisation experience;
- Knowledge of HDFS principles is expected, and familiarity with columnar storage formats like Parquet/ORC is an additional advantage;
- Prior experience in data warehousing modeling;
- Proficiency in programming languages such as Java, C++, and Scala is essential, along with strong coding skills and the ability to troubleshoot effectively;
Preferred Qualifications:
- Experience with other big data systems/frameworks like Hive, HBase, or Kudu is a plus;
- A willingness to tackle challenging problems without clear solutions, a strong enthusiasm for learning new technologies, and prior experience in managing large-scale data (in the petabyte range) are all advantageous qualities.
