Senior Data Engineer III

Shein Group; United States; On-site; USD 183,000 - 205,000; Full time

Job summary

SHEIN TECHNOLOGY LLC in San Diego, CA, is seeking a Sr. Data Engineer III to collaborate with global teams to design scalable data pipelines and ETL solutions. The role emphasizes data quality, security, and reliability across distributed systems, with on-call duties to ensure production stability.

Responsibilities include optimizing pipelines using Hive/Presto/Spark/Flink, managing Redshift-based warehousing, and ensuring data integrity in production within a cloud environment.

Qualifications

• Bachelor's degree in a related field plus four years of post-baccalaureate experience in data engineering.
• Experience building and optimizing large-scale distributed data pipelines with Hive, Presto, Spark, or Flink.
• Proficiency with data warehousing (Redshift) and SQL for large datasets.

Responsibilities

• Collaborate with global teams to analyze data requirements and design scalable data pipelines.
• ETL design, development, and maintenance across distributed systems with emphasis on data quality.
• Monitor pipelines for performance, reliability, and security; perform root cause analysis.
• Develop system architectures, documentation, and participate in on-call support.

Education

Bachelor’s degree

Tools

Hive

Presto

Spark

Flink

Amazon Redshift

AWS EMR

AWS S3

Airflow

Job description

Full-time or part-time: Full-time

Position Summary: SHEIN TECHNOLOGY LLC is seeking a Sr. Data Engineer III in San Diego, CA to collaborate with global teams across data, security, infrastructure, and business functions to analyze data requirements and design scalable data engineering solutions.

Job title: Sr. Data Engineer III

Job Location: 3111 Camino Del Rio N, Suite 1300, San Diego, CA 92108

Job Description:

Collaborate with global teams across data, security, infrastructure, and business functions to analyze data requirements and design scalable data engineering solutions. Design, develop, and maintain efficient and scalable data pipelines to extract, transform, and load (ETL) data across distributed systems. Apply data validation and quality assurance techniques to ensure the accuracy, consistency, and completeness of data throughout data processing workflows. Analyze and optimize data pipelines and processing jobs for performance, scalability, and reliability by identifying and addressing system-level inefficiencies. Ensure data integrity, security, privacy, and high availability through appropriate data modeling, access controls, and system architecture design. Monitor data pipelines and distributed data processing systems to identify abnormal behavior, diagnose technical issues, and implement corrective actions in production environments. Perform technical root cause analysis of data processing issues and collaborate with cross-functional teams to implement long-term, preventative solutions. Develop and maintain technical documentation for data pipeline designs, system architectures, and operational procedures, and communicate technical updates to stakeholders. Participate in a rotational on-call schedule to provide engineering-level support for critical data systems, ensuring production stability and reliability.

Minimum Education & Experience Requirements:

Bachelor’s degree or a foreign equivalent in Applied Data Science, Computer Science, or a related field, plus 4 years of post-baccalaureate experience in job offered or Data Engineering related job titles.

Requires 4 years of experience in:

• 1. Building and optimizing large-scale, distributed data pipelines with Hive, Presto, Spark, or Flink.
• 2. Data warehousing, including dimensional modeling, star/snowflake schema design, and normalization/denormalization strategies in large-scale data warehouses including Amazon Redshift.
• 3. Writing and optimizing complex SQL queries for large datasets, creating joins, aggregations, and subqueries, in the context of querying data warehouses.
• 4. Data storage solutions, including S3 on AWS.
• 5. Cloud-native services including AWS EMR, AWS S3.
• 6. Using workflow orchestration tools including Airflow in a production environment to automate, schedule, monitor and tune, data pipelines.

Salary range: $183,360 – $205,000