Data Engineer I, Amazon

Are you passionate about data and code Does the prospect of dealing with mission-critical data excite you Do you want to build data engineering solutions that process a broad range of business and customer data Do you want to continuously improve the systems that enable annual worldwide revenue of hundreds of billions of dollars If so then the eCommerce Services (eCS) team is for you!

In eCommerce Services (eCS) we build systems that span the full range of eCommerce functionality from Privacy Identity Purchase Experience and Ordering to Shipping Tax and Financial integration. eCommerce Services manages several aspects of the customer life cycle starting from account creation and sign in to placing items in the shopping cart proceeding through checkout order processing managing order history and post-fulfillment actions such as refunds and tax invoices. eCS services determine sales tax and shipping charges and we ensure the privacy of our customers. Our mission is to provide a commerce foundation that accelerates business innovation and delivers a secure available performant and reliable shopping experience to Amazons customers.

The goal of the eCS Data Engineering and Analytics team is to provide high quality on-time reports to Amazon business teams enabling them to expand globally at scale. Our team has a direct impact on retail CX a key component that runs our Amazon fly wheel.

As a Data Engineer you will own the architecture of DW solutions for the Enterprise using multiple platforms. You would have the opportunity to lead the design creation and management of extremely large datasets working backwards from business use cases. You will use your strong 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.

Key job responsibilities
Design implement and support a platform providing ad-hoc access to large data sets
Interface with other technology teams to extract transform and load data from a wide variety of data sources
Implement data structures using best practices in data modeling ETL/ELT processes and SQL Redshift and OLAP technologies
Model data and metadata for ad-hoc and pre-built reporting
Interface with business customers gathering requirements and delivering complete reporting solutions
Build robust and scalable data integration (ETL) pipelines using SQL Python and Spark.
Build and deliver high quality data sets to support business analyst data scientists and customer reporting needs.
Continually improve ongoing reporting and analysis processes automating or simplifying self-service support for customers

- 2 years of data engineering experience
- Experience with SQL
- Experience with one or more scripting language (e.g. Python KornShell)
- Experience with data modeling warehousing and building ETL pipelines
- Bachelors degree or equivalent

- Experience with big data technologies such as: Hadoop Hive Spark EMR
- Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions

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