Senior Data Engineer

We are looking for Senior Data Engineer to join us:
• 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.

• 13th Salary + Performance Bonus.
• Pass probation Bonus.
• Premium healthcare insurance benefits (PVI Insurance package) and family medical benefit (based on the level of experience).
• Provide the famous e-learning platform-Udemy, to encourage continuous learning to adapt to the T-shape model.
• Flexible working time: only 8 hours required as continual working-time at the office.
• Annual leave up to 17 days: 12 days paid leave + 5 days’ sick leave.
• Professional and Personal Development Training Programs.
• 4 Stars standard company trip in summer and a big annual Year-End-Party.
• Coffee and snacks provided.
• Holiday celebrations and parties for team members and family.

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical discipline.
• At least 5 years of experience in Data Engineering, particularly in Data Integration.
Technical Proficiency:
• Hands-on experience with Flink/Spark, Databricks, and preferably Kubernetes.
• Strong skills in SQL and Python programming.
• Familiarity with Big Data technologies such as Spark and Hadoop/MapReduce (preferred but not mandatory).
• Solid understanding of cloud platforms, including Azure, AWS, and Google Cloud Platform (GCP).
• Practical knowledge of Azure services like HDInsight and Azure Databricks would be advantageous.
• Good understanding of Linux, Iseries, and Windows operating systems.
• Knowledge of hosting solutions, container-based deployments, and storage architectures is beneficial.
Certifications:
• At least one recognized Big Data certification, such as Microsoft Certified: Azure Data Engineer Associate or AWS Certified Data Engineer – Associate.
• Additional certifications like Solution Architect are an advantage.
Other:
• Experience contributing to industry or open-source communities.
• Strong passion for analytics and machine learning technologies, a willingness to continuously learn, and effective.
• English communication skills.