Microsoft Data Engineer II 

Taiwan, Taoyuan City 

393734301

Required:

• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years’ experience in business analytics, data science, software development, data modeling or data engineering work OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, software development, or data engineering work OR equivalent experience.
• Experience working with cloud-based technologies, including relational databases, data warehouse, big data (e.g., Hadoop, Spark), orchestration/data pipeline tools, data lakes.
• Self-motivated and organized to deliver results

Preferred:

• Experience with Azure Analytics stack, e.g., Azure Data Lake, Azure Data Factory, Azure Synapse, Azure Data Explorer (Kusto), Azure Cosmos DB, Azure logic apps, Fabric/Power BI
• Experience in modern DevOps practices (including Git, CI/CD)
• Good interpersonal and communications (verbal and written) skills, including the ability to effectively communicate with both business and technical teams.

• Ability to use judgement and rating schemes to turn qualitative information into quantitative estimates
• Proficiency in scenario analytics, mining for insights

Responsibilities

• Work within and across teams to solve complex technical challenges
• Develop engineering best-practices – continuously evaluate our processes and reporting to identify opportunities to improve, enhance, and automate existing and new capabilities with a fundamental understanding of the end-to-end scenario
• Ability to use judgement and rating schemes to turn qualitative information into quantitative estimates
• Proficiency in scenario analytics, mining for insights
• Measure the success and usage patterns of the product / feature at various levels as well as key engineering metrics
• Contribute to a data-driven culture as well as a culture of experimentation across the organization.
• Creating dashboards in Power BI and Azure Data Explorer