Senior Big Data Engineer – Ecommerce Recommendation Infra

BYTEDANCE PTE. LTD.; Singapore; On-site; SGD 90,000 - 180,000; Full time

Job summary

ByteDance Singapore is seeking a skilled data engineering professional to join the E-commerce Recommendation Infra team. You will design offline data architectures and scalable storage systems to support advanced recommendation algorithms and ML applications.

Collaborating with applied machine learning engineers, you will ensure system stability, high availability, and efficient data processing for live services and analytics across massive datasets.

Qualifications

• Bachelor's degree or above in computer science, software engineering, or a related field.
• Experience with big data open source frameworks (Hadoop, Hive, Flink, Spark, Kafka, Elasticsearch).
• Proficiency in Java and C++ or other programming languages.
• Strong coding and troubleshooting abilities.
• Experience with large-scale data processing (PB level) is a plus.
• At least 3 years of relevant experience.

Responsibilities

• Design offline data architecture for large-scale recommender systems.
• Design scalable, high-performance storage and computing systems.
• Troubleshoot production systems and ensure stability.
• Build distributed storage and computing infrastructure.
• Develop analytics to transform raw data into meaningful information.
• Apply data mining, NLP, and ML to extract insights.
• Visualize and report data findings.

Skills

Strong coding

Troubleshooting

Java

C++

Education

Bachelor's degree or above in computer science/software engineering

Tools

Hadoop

Hive

Flink

Spark

Kafka

HBase

Redis

RocksDB

ElasticSearch

Job description

ByteDance Singapore is seeking a skilled data engineering professional to join the E-commerce Recommendation Infra team. You will design offline data architectures and scalable storage systems to support advanced recommendation algorithms and ML applications.

Collaborating with applied machine learning engineers, you will ensure system stability, high availability, and efficient data processing for live services and analytics across massive datasets.