Description 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 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 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 hypothesis to improve the business performance. Basic Qualifications - 1+ years of data engineering experience - 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Bachelor's degree in a quantitative/technical field such as computer science, engineering, 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 language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell) 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. 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. 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. This position will remain posted until filled. Applicants should apply via our internal or external career site.