Data Engineer II, ROW AOP

The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world. As a Data Engineer, you will play a crucial role in supporting the team by creating and maintaining the data infrastructure necessary for the advanced analytics and machine learning solutions.Key ResponsibilitiesDesign, develop, and maintain scalable data pipelines to support ML model development and production deployment.Implement and maintain CI/CD pipelines for the data and ML solutions.Collaborate with data scientists and other team members to understand data requirements and implement efficient data processing solutions.Create and manage data warehouses and data lakes, ensuring proper data governance and security measures are in place.Collaborate with product managers and business stakeholders to understand data needs and translate them into technical requirements.Stay current with emerging technologies and best practices in data engineering, and propose innovative solutions to improve data infrastructure and processes for ML models and analytics applications.Participate in code reviews and contribute to the development of best practices for data engineering within the team.Our Problem DomainUsing live package and truck signals to adjust truck capacities in real-timeHOTW models for Last Mile Channel AllocationUsing LLMs to automate analytical processes and insight generationOps research to optimize middle mile truck routesWorking with global partner science teams to affect Reinforcement Learning based pricing models and estimating Shipments Per Route for $MM savingsDeep Learning models to synthesize attributes of addressesAbuse detection models to reduce network lossesBasic QualificationsBachelor's degree or above in computer science, computer engineering, or related field, or Master's degree3+ years of data engineering experienceKnowledge of at least two of the following programming languages: Scala, Java, Python, C/C++, or GoExperience with SQL and an RDBMS (e.g., Oracle) or Data WarehouseKnowledge of cloud services such as AWS or equivalentKnowledge of data warehouse technical architecture, infrastructure components, ETL and reporting/analytic tools and environmentsExperience with version control systems and CI/CD pipeline implementationExperience in complex problem solving, and working in a tight schedule environmentExperience working in a collaborative team environment to deliver high-quality design solutionsPreferred QualificationsExperience in industry, consulting, government or academic researchExperience with training and deploying machine learning systems to solve large-scale optimizations, or experience in agile/scrum or related collaborative workflowExperience with automation and any version control tools, or experience in managing and troubleshooting network and experience in KafkaExperience working with data and analyticsExperience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.#J-18808-Ljbffr