• Experience in data engineering- 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)

In this role, you’ll be instrumental in developing automated performance evaluation systems and data engineering solutions for our machine learning models that drive millions in transportation cost savings. You’ll work at the exciting intersection of data engineering, software development, business intelligence, and machine learning operations. This position offers a unique opportunity to contribute to forecasting infrastructure, collaborate with cross-functional teams, and make a significant impact on Amazon’s global transportation network efficiency.Key job responsibilities• Design and implement scalable extract, transform, and load (ETL) processes.• Manage and maintain large datasets, production pipelines and jobs that that feed into or from critical demand forecasting models and reporting.• Work closely with senior engineers to drive data architecture.• Collaborate with product managers, data scientists and engineers to continually improve ongoing processes and to develop and improve the current data architecture, data quality, and data availability.• Manage and execute against project plans and delivery commitments.• Manage data infrastructure including AWS resources like S3, Redshift, Glue, etc.• Make recommendations to improve performance and/scalability either through updates based on a technical need or through innovation.About the teamOur team is a group of Scientists, Business Intelligence Engineers, Data Engineers, and Software Developers who build and maintain critical infrastructure for Amazon Transportation’s machine learning operations. We work at the intersection of scientific innovation, data engineering, ML systems, and business intelligence, developing solutions that enable rapid model development and reliable production deployments. Our team combines scientific expertise with engineering excellence to create automated performance evaluation systems, maintain data quality frameworks, and build scalable monitoring solutions. We’re passionate about using technology to solve complex problems and pride ourselves on fostering a collaborative environment where innovation and work-life harmony thrive.

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