Amazon
Data Engineer - Amazon Flex, Flex Analytics
Amazon, Seattle, Washington, us, 98127
Data Engineer - Amazon Flex, Flex Analytics
Interested in the gig economy? Come be a part of it. The Amazon Flex Analytics team is building a data 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 an outstanding Data Engineer who is passionate about data architecture and wants to 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 self-service analytics platform, defining metrics and KPIs, and automating reporting and data visualization.The successful candidate considers themselves an enterprise data architect. You should excel in the design, creation, and management of analytical data infrastructure. 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 a 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.RESPONSIBILITIES
Develop and improve the current data architecture using AWS Redshift, AWS S3, Spark, and Hadoop/EMR.Improve upon the data ingestion models, ETL jobs, and alarming to maintain data integrity and data availability.Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale for increasing data volumes.Partner with BIEs and Analysts across teams such as product management, operations, finance, marketing, and engineering to build and verify hypotheses to improve business performance.MINIMUM REQUIREMENTS
1+ years of data engineering experience.2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.Bachelor's degree in a quantitative/technical field such as computer science, engineering, or statistics.Knowledge of distributed systems as it pertains to data storage and computing.Experience with data modeling, warehousing, and building ETL pipelines.Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).Experience with one or more scripting languages (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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Interested in the gig economy? Come be a part of it. The Amazon Flex Analytics team is building a data 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 an outstanding Data Engineer who is passionate about data architecture and wants to 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 self-service analytics platform, defining metrics and KPIs, and automating reporting and data visualization.The successful candidate considers themselves an enterprise data architect. You should excel in the design, creation, and management of analytical data infrastructure. 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 a 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.RESPONSIBILITIES
Develop and improve the current data architecture using AWS Redshift, AWS S3, Spark, and Hadoop/EMR.Improve upon the data ingestion models, ETL jobs, and alarming to maintain data integrity and data availability.Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale for increasing data volumes.Partner with BIEs and Analysts across teams such as product management, operations, finance, marketing, and engineering to build and verify hypotheses to improve business performance.MINIMUM REQUIREMENTS
1+ years of data engineering experience.2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.Bachelor's degree in a quantitative/technical field such as computer science, engineering, or statistics.Knowledge of distributed systems as it pertains to data storage and computing.Experience with data modeling, warehousing, and building ETL pipelines.Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).Experience with one or more scripting languages (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 committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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