Data Engineer

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 Data Engineers to help us grow our Data Lake and Data Warehouse Systems, which are 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 include: developing and maintaining automated ETL pipelines using scripting languages such as Python, Spark, SQL, and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS; implementing and supporting reporting and analytics infrastructure for internal business customers; developing and maintaining data security and permissions solutions for enterprise scale data warehouse and data lake implementations; developing data objects for business analytics using data modeling techniques; developing and optimizing data warehouse and data lake tables using best practices; developing and maintaining data warehouse and data lake metadata, data catalogs, and user documentation for internal business customers; and working 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

About AWS

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.

Basic Qualifications

1+ years of data engineering experience

Experience with data modeling, warehousing and building ETL pipelines

Experience with one or more query language

Preferred Qualifications

Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

Experience with one or more scripting language

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.