Data Engineer - Real-Time Lakehouse & ML Infra

TikTok; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

TikTok Singapore is seeking a PhD-qualified engineer to help build the Arch-Data Ecosystem for large-scale data storage and ML infrastructure. You will design real-time and offline data architectures for recommendation, search, and advertising workloads, collaborating with ML platform teams.

This role involves optimizing lakehouse storage, managing metadata, and advancing streaming and batch processing with Flink and modern lakehouse technologies.

Qualifications

• PhD in AI, CS, software development or related field.
• Experience building large-scale distributed systems (storage/ML infra).
• Understanding of Flink internals and state management.
• Familiar with Lakehouse tech (Paimon/Iceberg/Delta Lake/Hudi).

Responsibilities

• Design real-time and offline data architecture for large-scale recommendation systems.
• Build scalable streaming Lakehouse systems powering feature pipelines and real-time inference.
• Collaborate with ML platforms to support PyTorch training workflows and data formats.
• Own components of distributed storage and processing stack from file formats to metadata.

Skills

Distributed systems

State management

Flink internals

Model training pipelines

PyTorch integration

Education

PhD in AI/CS/Software

Tools

Apache Flink

Paimon

Iceberg

Delta Lake

Hudi

Parquet

ORC

Lance

HBase

Kudu

Java/Scala/C++

Job description

TikTok Singapore is seeking a PhD-qualified engineer to help build the Arch-Data Ecosystem for large-scale data storage and ML infrastructure. You will design real-time and offline data architectures for recommendation, search, and advertising workloads, collaborating with ML platform teams.

This role involves optimizing lakehouse storage, managing metadata, and advancing streaming and batch processing with Flink and modern lakehouse technologies.