Data Analytics Engineer (ETL & Data Warehouse, 40K)

By coordinate with different teams to troubleshoot, solve problems, and improve ETL pipelines and data warehouse architecture. The ideal candidate will have strong analytical skills, good communication, and a solid understanding of how all the systems connected to the data warehouse work together.

• Collaborate with technical teams, developers, data users, and business teams to ensure smooth implementation.
• Develop use cases by gathering and validating business requirements through workshops.
• Manage stakeholder expectations and resolve client issues efficiently.
• Design and model ETL data structures, storage, and integration processes. Ensure data quality, integrity, and proper exception handling.
• Write technical documentation for system requirements and specifications.
• Design scalable data models to support growth while minimizing risks and costs.
• Evaluate new data sources for quality and understand how they impact existing pipelines.
• Troubleshoot data discrepancies and develop scalable solutions to bridge business needs and ETL processes.

Requirements:

• Bachelor’s degree or higher in computer science, engineering, or related fields
• 5+ years IT experience, with 2+ years in data migration, BI, or data warehousing, with hands-on SQL experience (Oracle or SQL Server), Power BI, including report building and data management
• Familiar with data modeling (Star Schema, Snowflake) and Power BI security
• Knowledge of data quality, modeling, and architecture
• Experience in Hadoop, Python, Java Spring Boot, Docker, JSON API, M scripting is a PLUS
• Fluent in English and Chinese (Mandarin/Cantonese)