數據工程師 Data Engineer

6146

客戶的成功 才是SHOPLINE的成功


名稱: SHOPLINE

地區:台北

地址: 東興路45號6樓, 信義區台北市110

公司規模:110人

工作內容

At SHOPLINE we are working on very intenteresting initiatives that would involve using data-mining and `machine learning`. with the vast amount of data that we currently have and growing exponentially. We will share details during the interview.

[About this job]
1. Develop, operate, and monitor ETL for data collection, cleansing, processing, storage, and analytics
2. Develop data visualization to track data usage, server status, and represent data insights
3. Automate data process tasks and support data analysis tasks
4. `Use existing` algorithms and implement data-mining strategies to achieve our end goal.

條件要求

[About you]
1. At least 2 years of experience in building and operating large scale distributed systems or applications
2. At least 2 years of experience in processing data with Python `(scikit-learn)`
3. Experience with implementing highly scalable systems on top of cloud infrastructures, such as AWS or GCP
4. Expertise in Linux/Unix environments and familiar with shell scripting
5. Expertise in hands-on ETL job design, components and modules development of data process with Airflow
6. Great communication skill and can-do attitude
7. Desired skills: Python `(scikit-learn)`,Linux/Unix, AWS, Mongo/PostgreSQL, Airflow, BigQuery

[Plus]
1. Data mining and machine learning algorithm experience is a big plus

公司福利

1.彈性工作時間 / Flexible work hours
2.彈性工作地點 / Flexible work location
3.第一年即享有12天年假 / First year 12 days of annual leave
4.給薪病假 / Full pay sick leave
5.給薪家庭照顧假 / Paid family care leave
6.給薪緊急事件假 / Paid Emergency leave
7.產假90天 / Maternity leave 90 days
8.陪產假14天 / Paternity leave 14 days
9.公司贊助旅遊基金$20,000 / Company sponsored trips
10.公司贊助訓練補助$20,000 / Company sponsored Training
11.季度部門聚餐補助$ 1,000 / Company sponsored team quarterly dinner
12.平等的公司成員架構 / Flat team structure
13.優質薪資待遇 / Competitive salary package
14.有機會驅動產品導向,只要你有好的想法! / Ability to drive product direction

薪資範圍

NT$ 30,000 - (月薪)

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