Description

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. You’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

We’re looking for an experienced Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! We own a world-class data lake that is used to drive multi-billion dollar decisions on a regular cadence and we're looking to improve on filling the lake quickly, with as little human intervention needed and democratize the data in the lake.

Our Data Engineers build the ETL and analytics solutions for our internal customers to answer questions with data and drive critical improvements for the business. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. We are passionate about solving business problems with data!

Key job responsibilities
- Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.
- Implement and support reporting and analytics infrastructure for internal business customers.
- Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging.
- Develop data objects for business analytics using data modeling techniques.
- Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.
- Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.
- Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions.

About the team
https://w.amazon.com/bin/view/CDPA/BI/BIE_Team_LP/