Amazon Data Engineer Partner Intelligence 

United States, Washington, Seattle 

143802084

Sales, Marketing and Global Services (SMGS)
Key job responsibilities
• Architecture design and implementation of next generation data pipelines and BI solutions
• Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
• Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
A day in the life
• Collaborate with Software Engineers, Product Managers, Data Scientists and Business Intelligence Engineers to design, plan and deliver on high priority data initiatives serving internal stakeholders and AWS customers.
• Build automated, fault tolerant and scalable data solutions leveraging state of the art technologies including but not limited to Spark, EMR, Python, Redshift, Glue and S3.
• Look around corners and be creative - Continuously evaluate and improve our strategy, architecture, tooling and codebase to maximize performance, scalability and availability.Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred 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 AWSWork/Life BalanceInclusive Team CultureMentorship and 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.

- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.