Big Data Engineer — Recommendation Architecture & Scale

TikTok; San Jose (CA); On-site; USD 128,000 - 317,000; Full time

Benefits offered by this job

Health benefits

401(k) match

Parental leave

Paid holidays

Sick days

Paid personal time

Job summary

TikTok is seeking a highly capable candidate to join the Recommendation Architecture Team. You will help design offline data architecture and scalable storage for a massive recommender system, while ensuring stability and high availability of distributed data pipelines.

The role emphasizes implementing high-performance storage and compute systems, applying ML and data analytics to derive actionable insights, and building end-to-end solutions for large-scale data processing within a fast-growing

Qualifications

• Bachelor's degree in CS or related field is required.
• Familiar with open-source big data frameworks listed above.
• Proficient in Java and C++, with strong debugging skills.
• Demonstrated ability to learn new technologies quickly.
• Willing to tackle difficult, open-ended questions.

Responsibilities

• Design and implement offline data architecture for large-scale recommender systems.
• Design scalable, high-performance storage and computing systems.
• Troubleshoot production systems and ensure operational stability.
• Build distributed storage/computing infrastructure for massive data.
• Develop analytics applications to transform raw data into insights.
• Apply data mining, NLP, and ML to extract information from large datasets.
• Visualize and report data findings; may create dynamic data reports.

Skills

Java

C++

Big data frameworks

Troubleshooting

Learning mindset

Education

Bachelor's degree in Computer Science or related

Tools

Hadoop

Hive

Flink

FlinkSQL

Spark

Kafka

HBase

Redis

RocksDB

Elasticsearch

Job description

TikTok is seeking a highly capable candidate to join the Recommendation Architecture Team. You will help design offline data architecture and scalable storage for a massive recommender system, while ensuring stability and high availability of distributed data pipelines.

The role emphasizes implementing high-performance storage and compute systems, applying ML and data analytics to derive actionable insights, and building end-to-end solutions for large-scale data processing within a fast-growing