Big Data/Cloud Data

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

Yêu cầu ứng viên

Knowledge:

• Knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce is desirable but not essential.
• Knowledge of Azure services like HD Insight, Azure DataBricks etc.
• Working knowledge of the pros, cons and usages of various ML/DL applications (such as Keras, Tensorflow, Python scikit learn and R).
• 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.
• Knowledge on Linux, Iseries, Windows.

Qualifications:

• 2 years of experience with Flink/Spark, Databricks and ideally Kubernetes.
• 2 years of experience with Azure (DP200 and/or DP201, DP203 certification acts as a plus).
• Good knowledge of SQL and excellent coding skills (Python).
• Passionate about analytics machine learning technology & applications and eager to learn.
• English communication.

Quyền lợi được hưởng

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