Data Engineer , Retail Business Service

Job summary:

Retail Business Services (RBS) supports Amazon’s Retail business growth WW through three core tasks: (a) Selection, where RBS sources, creates and enriches ASINs to drive GMS growth; (b) Defect Elimination, where RBS resolves inbound supply chain defects and develops root cause fixes to improve free cash flow; and (c) supporting operational processes for WW Retail teams. Our team of high‑caliber software developers, applied scientists, data engineers, product managers, and Business Intelligence Engineers use rigorous ML and deep learning approaches to ensure we identify and fix the right catalog defect to provide a good shopping experience for our customers.

As a Data Engineer, you will own and deliver data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You strive for simplicity, demonstrate creativity and sound judgment. You deliver data solutions that are customer focused, easy to consume, and create business impact. You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics.

You have a strategic and long‑term view on architecting advanced data ecosystems. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases and applications.

• Implement data ingestion routines both real-time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
• Design, implement and operate large‑scale, high‑volume, high‑performance data for analysis and data science.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self‑service modeling and production support for customers.

• 1+ years of data engineering experience
• Experience with SQL
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, Spark
  
  SQL, Scala)
• Experience with one or more scripting languages (e.g., Python, Korn Shell)

• 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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