Data Engineer

The data platforms include relational databases, nonrelational databases, data streams, and file stores
Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines
Responsible for using Databrick to build model in Datalake/Azure Synapse
Responsible for implementing robust data pipeline using Azure Stack
Responsible for creating reusable and scalable data pipeline
Manage and secure the flow of structured and unstructured data from multiple sources.
Data engineers’ provision and set up data platform/Streaming data technologies that are on- premises and in the cloud.

Working knowledge of the pros, cons and usages of various ML/DL applications (such as Keras, Tensorflow, Python scikit learn and R)
Knowledge on Linux, Iseries, Window
Contribution to industry/open source communities.
Knowledge and practical experience of cloud- based platforms and their ML/DL offerings (such as Google GCP, AWS, and Azure) would be advantageous
Understanding of infrastructure (including hosting, container- based deployments and storage architectures) would be advantageous
Experience with Databricks, data modeling, and Power BI
Knowledge of Azure services like HD Insight, Azure DataBricks etc.
Knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce is desirable but not essential

Bảo hiểm xã hội, Bảo hiểm y tế
Trang bị hiện đại: Laptop làm việc tiên tiến, hỗ trợ công cụ đầy đủ
Đánh giá minh bạch, công bằng
Tăng lương định kỳ: Review lương dựa trên năng lực và kết quả công việc hàng năm
Nhân viên được hưởng lương tháng 13 và thưởng các dịp lễ, Tết- theo chính sách công ty từng năm

Cập nhật gần nhất lúc: 2026-03-03 19:25:02