Lead, design, enhance, and maintain overseas data warehouse and data platform solutions across mobile device, IoT, application, and business data domains.
Develop scalable batch and real-time data pipelines using SQL, Spark, Flink, Hadoop ecosystem tools, and related big data technologies.
Build reliable data models and warehouse layers, including ODS, DWD, DWS, and ADS, to support analytics, reporting, and business decision-making.
Optimize distributed data processing workflows to improve performance, stability, scalability, and efficiency.
Establish data governance practices covering data quality, lineage, metadata, standards, and consistency across integrated data sources.
Create dashboards, visualization tools, reports, and data products that convert complex data into clear business insights.
Collaborate with business, product, analytics, and engineering teams to translate requirements into practical and maintainable data solutions.
Required Skills and Qualifications
Bachelor’s degree or above in Computer Science, Data Engineering, Information Systems, or a related field.
At least 5 years of experience in data engineering, data platform development, or large-scale data warehouse implementation.
Strong hands-on experience with SQL, Spark, Flink, Hadoop, data modeling, and structured or unstructured data processing.
Proven ability to design high-volume data warehouses and optimize data pipelines for performance, reliability, and usability.
Experience building dashboards, reporting platforms, visualization solutions, and business-facing data applications.
Good communication skills with the ability to work effectively with technical and non-technical stakeholders.
Preferred Skills
Experience supporting overseas or global data environments is preferred.
Mandarin proficiency is preferred as required to collaborate with counterparts.