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.
As a Data Engineer, you should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms.
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 analysts and engineers to determine how best to design the data warehouse for reporting and analytics.
You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making.
You should have the ability to develop and tune SQL to provide optimized solutions to the business., Experience writing high quality, maintainable SQL on large datasets.
Ability to write code in Python, Ruby, Scala or other platform-related Big data technology.
Expertise in Star Schema data modelling
Exposure / Experience in Big data Technologies (hadoop, spark, etc.).
Strong analytical and problem solving skills
Expertise in the design, creation and management of large datasets / data models
Experience working on building / optimizing logical data model and data pipelines while delivering high data quality solutions that are testable and adhere to SLAs
Experience with AWS services including S3, Redshift, EMR and RDS
Excellent verbal and written communication skills
Ability to work with business owners to define key business requirements and convert to technical specifications
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
Experience working with other engineers in defining data engineering best practices and leveraging software development life cycle best practices such as agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations