Data Engineer, Japan Consumer Innovation (JCI), JP Science and Data Technologies Job at Amazon Japan G.K., 東京都

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  • Amazon Japan G.K.
  • 東京都

Job Description

DESCRIPTION

Are you passionate about working with data and eager to make broad business impact in the rapidly evolving e-commerce business? Are you interested in building data and science solutions to drive strategic direction? Based in Tokyo, the Science and Data Technologies team designs, builds, operates, and scales the data infrastructure powering Amazon's retail business in Japan. Working with a diverse, global team serving customers and partners worldwide, you can make a significant impact while continuously learning and experimenting with cutting-edge technologies. The ideal data engineer thrives on working with large-scale data, excels in highly complex technical environments, and above all, has a passion for data. You will lead the development of data solutions to optimize Amazon's retail operations in Japan, turning business needs into robust data pipelines and architecture. Leveraging your deep experience in data infrastructure and passion for enabling data-driven business impact, you will work closely with scientists, software engineers and business teams to identify and implement strategic data opportunities.

Key job responsibilities
Your key responsibilities include:
- Create data solutions with AWS services such as Redshift, S3, EMR, Lambda, SageMaker, CloudWatch etc.
- Implement robust data solutions and scalable data architectures.
- Develop and improve the operational excellence, data quality, monitoring and data governance.

BASIC QUALIFICATIONS

- Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline.
- 3+ years of experience as a Data Engineer or in a similar role.
- 3+ years of experience with data modeling, data warehousing, ETL/ELT pipelines and BI tools.
- Experience with cloud-based big data technology stacks (e.g., Hadoop, Spark, Redshift, S3, EMR, SageMaker, DynamoDB etc.)
- Knowledge of data management and data storage principles.
- Expert-level proficiency in writing and optimizing SQL.
- Ability to write code in Python for data processing.
- Business level English (written and verbal)

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