Data Engineer Graduate(TikTok Recommendation Ecosystem Architecture) - 2027 Start (PhD)
Core
Design and implement real-time and offline data architecture for large-scale recommendation systems, building scalable streaming Lakehouse systems to power feature pipelines and model training.
Role type
Senior IC data engineer (recommendation ecosystem)
Builds
Unified infrastructure integrating training data bases and state systems for multimodal foundation models in search, recommendation, and advertising
Domain
Internet / Recommendation Systems / Distributed Data Infrastructure
Deliverable
production ML models
Required skills
Large-scale distributed systems design, Apache Flink internals, Lakehouse technologies (Apache Paimon, Iceberg, Delta Lake, Hudi), PyTorch integration, Java/Scala/C++, columnar file formats (Parquet, ORC, Lance)
Preferred skills
Flink + Paimon architecture optimization, feature storage pipelines, Lakehouse metadata management, legacy data stores (HBase/Kudu)
Technologies
Apache Flink, Apache Paimon, Apache Iceberg, Delta Lake, Hudi, PyTorch, Parquet, ORC, Lance, HBase, Kudu
Responsibilities
Design real-time and offline data architecture for large-scale recommendation systems; Build scalable streaming Lakehouse systems; Collaborate with ML platform teams to support PyTorch-based model training workflows; Own core components of distributed storage and processing stack
Seniority
Graduate (PhD), entry-level IC
