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Join Amazon's Selling Partner Insights and Analytics (SPIA) organization as a Data Engineer, where you'll build the data infrastructure powering 200+ business teams across Amazon Stores. Shape the future of data engineering for a platform processing millions of cases daily, driving insights that directly impact customer experience and operational excellence across the world's largest e-commerce ecosystem.
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, 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.
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 datasets
4. Design and implement scalable and cost effective data infrastructure to enable Non-IN(Emerging Marketplaces and WW) use cases on our data platform
5. 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 technologies
6. 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 operations
8. Enjoy working closely with your peers in a group of very smart and talented engineers.
A day in the life
A day in the life of Data Engineer is equally interesting and challenging. The interesting part is learning about business, ever expanding databases and codebases, internal tech stack for builders, AWS and many more. The challenging part of a data engineer's life is to apply these learnings in building robust and reliable data applications. A DE will be involved in driving both business and technical related discussions and making several key decisions contributing to the success of Selling Partner Operations and Business teams.
About the team
Selling Partner Insights and Analytics team's (SPIA) vision is to provide data and insights to accelerate stakeholder's data-driven decisions. Our mission is to make it easier and faster for our internal customers to use analytics to shorten the path from data to insights
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Our 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 for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Job ID: 148636001
Skills:
Hiveql, Sql, SSIS, Ddl, Pl Sql, Emr, Datastage, Hadoop, Bodi, Hive, Sparksql, Python, Informatica, Odi, Scala, Spark, KornShell, MDX
Skills:
Nosql, Gcp, Apis, Docker, Azure, Python, Sql, Kubernetes, AWS, time-series database systems
Skills:
Data Modeling, Data Warehousing, Sql, Git, Gcp, Spark, Databricks, Azure, Python, AWS, BI tools integration, ETL pipelines
Skills:
Data Governance, ETL frameworks, quality assurance practices, data integration techniques, Microsoft Azure Databricks, building scalable data pipelines, managing large datasets, cloud-based data storage and processing solutions
Skills:
Power Bi, MySQL, Postgres, Sql, Airflow, dbt, Dataform, Looker
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