Data Engineer

Yes4All is one of the leading brands for home sporting goods & furniture in the e-commerce market. Founded in 2010, we have strived to be in the top 1% retailers on Amazon US. Based in California with an operation office in HCMC, we have more than 400 young and talented members with expert knowledge and experience in the e-commerce industry.

We are on an ambitious journey to dominate not only Amazon's sporting goods market but also to enter new e-commerce markets from many regions like Canada, Europe, Japan. Besides, Home sporting goods, Furniture, Outdoor and Gardening are also great opportunities that we desire to occupy and create significant values. With our steady knowledge in E-commerce, Yes4All started to provide end to-end ecommerce-enabler service in order to help Vietnamese and global manufacturers or struggling sellers bring their products to the US & International markets.

JOB DESCRIPTIONS

• Responsible for industrialization, deployment and functional maintenance of data products/solutions, including digital products, business intelligence, and machine learning use cases.
• Collaborate with other member and user to build Data Pipelines.
• Responsible for quality checking and testing.
• Collaboratively work to solve research problems.
• Develop new algorithms and computational tools to solve research problems.
• Review research code created by other team members.
• Write technical documentation and reports.
• Continue learning new technologies, introducing existing products, improving product experience, and creating more value.

SKILL AND EXPERIENCE

-  At least 1 year experiences in Data Engineer.

-  Demonstrable experience in web application development (building of API driven interfaces).

-  Ability to program with Python is required.

-  Good knowledge in data warehouse, ETL, Data Pipeline.

-  Proficiency in SQL.

-  Exposure to emerging open-source technologies is preferred.

-  Good number sense, logical thinking, problem-solving and communication skills.

-  Have teamwork skills, work independently and self-study.

-  Experience with data pipeline and workflow management tools: Airflow, etc.

-  Experience with big data tools: Spark, Kafka, etc.

-  Experience with Oracle.