Amazon Data Engineer Selling Partner Experience AI initiatives 

United States, Washington, Seattle 

835564255

You must be able to prioritize and work well in an environment with competing demands. This role requires a high degree of ownership and a drive to solve some of the most challenging data and analytic problems in retail. Candidates must have demonstrated ability to manage large-scale data modeling projects, identify requirements and tools, build data warehousing solutions that are explainable and scalable. In addition to the technical skills, a successful candidate will possess strong written and verbal communication skills and a high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise.
Key job responsibilities
- Implement and support an analytical data infrastructure
- Manage AWS resources including EC2, EMR, S3, Glue, Redshift, etc.- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Maintain internal reporting platforms/tools including troubleshooting and development. Interact with internal users to establish and clarify requirements in order to develop report specifications.
- Work with Engineering partners to help shape and implement the development of BI infrastructure including Data Warehousing, reporting and analytics platforms.- Write advanced SQL queries and Python code to develop solutionsA day in the life
This role requires you to live at the intersection of data, software, and analytics. We leverage a comprehensive suite of AWS technologies, with key tools including S3, Redshift, DynamoDB, Lambda, API's, Glue.
You will drive the development process from design to release.

- 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, KornShell)

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