Data Engineer II

This job is with Amazon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.DESCRIPTION: Paragon is a case management system (CMS) used by 180+ business teams within Stores to manage their communications and interactions with their customers. These business teams using Paragon are our enterprise customers. Paragon CMS includes: a customizable workbench UI, a lifecycle manager, a routing layer, cross-cutting services such as tenant configuration, case storage, security, and data insights and analytic. The successful candidate is expected to contribute to all parts of the data engineering and deployment lifecycle, including design, development, documentation, testing and maintenance. They must possess good verbal and written communication skills, be self-driven and deliver high quality results in a fast paced environment. You will thrive in our collaborative environment, working alongside accomplished engineers who value teamwork and technical excellence. We're looking for experienced technical leaders. The successful candidate is expected to contribute to all parts of the data engineering and deployment lifecycle, including design, development, documentation, testing and maintenance. They must possess good verbal and written communication skills, be self-driven and deliver high quality results in a fast paced environment. You will thrive in our collaborative environment, working alongside accomplished engineers who value teamwork and technical excellence. We're looking for experienced technical leaders.Key job responsibilities 1. Design/implement automation and manage our massive data infrastructure to scale for the analytics needs of case management.2. Build solutions to achieve BAA(Best At Amazon) standards for system efficiency, IMR efficiency, data availability, consistency & compliance.3. Enable efficient data exploration, experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets4. Design and implement scalable and cost effective data infrastructure to enable Non-IN(Emerging Marketplaces and WW) use cases on our data platform5. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, Amazon and AWS big data technologies6. Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.7. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations8. Enjoy working closely with your peers in a group of very smart and talented engineers. BASIC QUALIFICATIONS: - 3+ years of data engineering experience - Experience with SQL - Experience with data modeling, warehousing and building ETL pipelines - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - 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 PREFERRED QUALIFICATIONS: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience building large-scale, high-throughput, 24x7 data systems - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience providing technical leadership and mentoring other engineers for best practices on data engineeringOur inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.