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. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
As a Data Engineer on our team, you'll work with technologies and complex data environments. You'll be responsible for enhancing our existing data architecture to further standardize metrics and definitions, developing end-to-end data engineering solutions for complex analytical problems, and collaborating with business intelligence engineer, and software engineers to translate data into actionable insights.
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.
A day in the life Imagine a day where you're not just managing data, but crafting intelligent systems that tell compelling stories. You'll dive into intricate data landscapes, designing pipelines that seamlessly connect AWS Data Center datasets, optimize performance, and unlock hidden patterns. Your work will involve:
- Exploring innovative data transformation techniques - Developing intelligent, automated reporting solutions - Collaborating with cross-functional teams to solve complex analytical challenges - Researching emerging technologies that could revolutionize our data strategy