Data Engineer, Flex Analytics

- 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.

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Interested in the gig economy? Come be a part of it. The Amazon Flex Analytics Team is building the global business intelligence platform that powers Amazon Flex worldwide. We’re working hard, having fun, and making history!

We are looking for candidates who want to help shape the future of Flex. Specifically, we are looking for a Data Engineer who is passionate about data architecture and wants help us use data to understand Flex Driver behavior and satisfaction. In this role, you will develop and support the analytic technologies that give our teams flexible and structured access to their data, including implementation of a BI platform, defining metrics and KPIs, and automating reporting and data visualization.

You will be responsible for designing and implementing scalable processes to publish data and build solutions to reconcile data for integrity and accuracy of data sets used for analysis and reporting. You should have broad understanding of RDBMS, ETL, Data Integration, Data Warehousing, Data Governance and Data Lakes. Experience with Python, R, or Spark is highly preferred and will put you at the top of the list.

Key job responsibilities
In this role, you will have the opportunity to use your skills in the following areas:

* Create and support data pipelines built on Amazon and AWS technologies including Spark, Cradle, DataCraft, Glue, Kinesis, and Redshift/Spectrum
* Develop and improve the current data architecture, data quality, monitoring and data availability
* Collaborate with BI Engineers to continually improve ongoing reporting and analysis processes, simplifying self-service support for customers
* Design, implement, and support platforms that provide business teams ad-hoc access to large datasets (ex. data visualization tools for non-tech business users)
* Participate in strategic and tactical planning discussions that drive the DE team’s work