Amazon.com operates in a virtual, global e-commerce environment without boundaries, and operates a diverse set of businesses, including retail, third party marketplaces, e-
commerce platforms, web services for developers. Amazon's mission is to be earth's most customer-centric company. Compliance Operations (C-
Ops) is part of Health Safety Sustainability Security and Compliance (HSSSC) organization within Amazon. C-Ops ensures that Amazon transactions satisfy legal and safety requirements in compliance with guidelines set by regulatory bodies.
We coordinate with aspects of identifying the risk involved in handling a hazardous product while storage and transport and classifying products with appropriate hazmat attributes.
This team also review aspects of product transactions that are regulated (distribution, shipping, sale, and import / export).
This involves analyzing product import documentation. We focus on product testing, certification, and regulatory permitting to ensure customer safety and protect Amazon in a constantly changing global environment.
This role requires an individual with excellent analytical abilities as well as outstanding business acumen and comfort with technical teams and systems.
Candidate should have a strong attention to detail and an ability to work in a fast-paced and ever-changing environment
As an Amazon.com Data Engineer you will be working in one of the world's largest and most complex data warehouse environments.
You should be an expert in the architecture of DW solutions for the Enterprise using multiple technologies (RDBMS, Columnar, Cloud).
You should excel in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions.
Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.
Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.
pipeline and other big data technologies