Data Engineer III, Amazon Manufacturing Services; AMS

Job :  |  Services LLC

Do you want to turn manufacturing data into decisions that move physical parts through a factory? Amazon Manufacturing Services (AMS) runs 135+ machines producing custom parts for over 100 Amazon organizations, and nearly every machine, order, and operator action generates data worth analyzing. You will join a small, growing data engineering team that owns the pipelines, warehouse, dashboards, and ML workflows that turn raw signals from our services and enterprise systems into throughput, utilization, and quality insights for shop floor users and AMS leadership.

The scope is broad, the stakeholders are in the building, and your models will influence how Amazon makes things.

• Design and operate data pipelines on AWS Glue (PySpark), Kinesis, S3, and Event Bridge to ingest DynamoDB streams and enterprise system data into the AMS data lake
• Model and maintain the Redshift warehouse and S3/Athena data lake that power analytics across AMS services
• Build ingestion and modeling layers for enterprise data sources including SAP S/4
  
  HANA, Job Boss, Siemens Teamcenter, and Dot Compliance
• Develop Quick Sight dashboards for shop floor operators, planners, and AMS leadership, covering operational metrics and executive KPIs
• Build and deploy ML models and pipelines for manufacturing use cases such as demand forecasting, machine health prediction, and scheduling optimization
• Own data quality, lineage, and documentation across the AMS analytics stack
• Collaborate with senior SDEs on architecture, service event schemas, and integration patterns, while holding significant ownership over your part of the data domain

Your day starts with a standup alongside SDEs, data engineers, and manufacturing stakeholders. You pick up where you left off on a React component that displays real-time resource status for shop floor planners. After lunch, you shift to a backend service, designing a DynamoDB schema for part versioning. A code review comes in from a senior engineer working on an enterprise integration bridge, and you spend time understanding how AMS connects to external manufacturing platforms.

Some weeks lean more frontend — building interactive data visualizations or responsive layouts for shop floor devices. Other weeks lean more backend — implementing event-sourced entity patterns or integrating with third-party APIs. The mix depends on the sprint and your strengths.

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you're passionate about this role and want to make an impact on a global scale, please apply!

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices

• Experience with big data technologies such as:
  Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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…