AWS is one of Amazons largest and fastest growing businesses serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial analytical creative flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced innovative team that is making history this is the place for you. The AWS Finance Analytics and Science Team supports the BI needs of the AWS Worldwide Specialist Organization a world-wide team of sales and technical specialists responsible for selling AWS most advanced services. The successful candidate will be an expert with SQL ETL (and general data wrangling) and have exemplary communication skills. The candidate will need to be comfortable with ambiguity in a fast-paced and ever-changing environment and able to think big while paying careful attention to detail. The candidate will be passionate about working with huge data sets and someone who loves to bring data together to answer business questions and drive growth.
Key job responsibilities This role builds and continuously improves data models processes and mechanisms that provide business intelligence for AWS. The role will work with executives program owners finance and technical peers to execute on large-scale projects that drive step change growth for the business. This role will help develop and implement data engineering best practices for the team in partnership with other engineers scientists and economists. The role will also be an important collaborator with other technical and business teams at AWS.
A day in the life Our team takes big swings and works on really hard cross-organizational problems. We ask people to grow their skills and stretch and we do it in a supportive and fun environment. Its about empirically measured impact advancement and fun.
About the team Our group is technically rigorous. Our leaders are here for you and to enable you to be successful. We are communication centric since being able to explain what we do ensures high success rates and lowers administrative churn. And if its not fun whats the point
- 2 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
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