Data Engineer - Global E-Commerce (Governance Service - Security Platform)

Description

Global E-Commerce is a content e-commerce business with international short video product as the carrier. It is committed to becoming the first choice for users to discover and purchase good products with affordable prices. Global E-Commerce business team hopes to provide users with more tailored and efficient consumption experience, enabling merchants to receive reliable platform services in different scenarios such as live e-commerce, short video content e-commerce, thereby making more affordable and high-quality products easily accessible and improving lives.

The Global E-Commerce's Governance and Experience is a global team responsible for ensuring a safe and trustworthy marketplace not only for our buyers but also for our sellers and creators. We continually work on areas such as risk detection abilities, fairness, and sustainability of the E-Commerce ecosystem, content and commodity quality, and friction-free experiences to drive improvement.

Responsibilities:
- Responsible for the offline data warehouse construction of global e-commerce security, including data layering, model design, ETL process, etc.
- Establish data warehouse standards for global e-commerce security to ensure data accuracy and consistency.
- Collaborate with the security team in optimising their offline tasks to ensure system stability and improving resource efficiency.
- Assist in identifying risk indicators through data analysis to support the development of key security projects.
- Support real-time data processing pipelines, including tagging systems and real-time ETL infrastructure.
- Visualise, interpret, and report data findings and may create dynamic data reports as well.

Requirements

Minimum Qualifications:
- Bachelor's or higher degree in Computer Science, Information Technology, Programming & System Analysis, Science (Computer Studies) or related discipline.
- Candidates should have at least 5 years of experience in big data ecosystem development, familiar with technologies such as Spark, Flink, Clickhouse, Hadoop, and practical experience with Lambda/Kappa architectures.
- Proficient in data warehouse implementation methodologies, with a deep understanding of data warehouse systems, and experience supporting real-world business scenarios.
- Experience in SQL performance tuning, with an understanding of Hive SQL development.

Preferred Qualifications:
- Candidates with deep experience in real-time data warehouse construction.
- Data-sensitive with strong business understanding, excellent logical reasoning skills, and some data analysis capabilities.