Amazon Logistics is looking for a customer focused, analytically and technically skilled Data Engineer to build advanced data and reporting solutions for AMZL leadership and BI teams.

This position will be responsible for building and managing real time data pipelines, maintaining reporting infrastructures, work on complex automation pipelines leveraging AWS and building analytical tools to support our growing Amazon Logistics business in Japan.

The successful candidate will be able to effectively extract, transform, load and visualize critical data to improve the latency and accuracy of the existing data pipelines and drive faster analytics through data.

This individual will work with business, software development and science teams to understand their data requirements and ensure all the teams have reliable data that drives effective business analytics. This role requires an individual with software development and data warehouse skills.

• Key job responsibilities
• Own the design, development, and maintenance of last mile data sets
• Manipulate/mine data from database tables (Redshift, Apache Spark SQL)
• Conduct deep dive investigations into issues related to incorrect and missing data
• Identify and adopt best practices in developing data pipelines and tables: data integrity, test design, build, validation, and documentation.
• Continually improve ongoing reporting and data processes in AMZL
• Work with in-house scientists, global supply chain, transportation and logistics teams, and software teams to identify new features and projects.
• Identify ways to automate complex processes through AWS.
• This is an individual contributor role that will partner with internal stakeholders across multiple teams, gathering requirements and delivering complete solutions
  Internal job description

Basic Qualifications

• Undergraduate or graduate students graduating in2027
• Speak, write, and read fluently in both Japanese and English
• 1+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, Korn Shell)

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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