AmazonPosted 1w ago

Data Engineer III, Amazon Manufacturing Services (AMS)

Data Engineer III, Amazon Manufacturing Services (AMS) at Amazon scores 65 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Bellevueseniorfull-time$155k-$209k

AI in this role

Build data pipelines, data warehouses, and machine learning models for manufacturing operations and analytics at Amazon.

aws-gluepysparkkinesiss3eventbridgedynamodbredshiftathenasapquicksightreact

data-engineeringml-pipelinesetldashboardingsql

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.

Key job responsibilities
- Design and operate data pipelines on AWS Glue (PySpark), Kinesis, S3, and EventBridge 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/4HANA, JobBoss, Siemens Teamcenter, and Dot Compliance
- Develop QuickSight 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

A day in the life
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.

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 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!

Basic qualifications

- 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

Preferred qualifications

- 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 process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 154,600.00 - 209,100.00 USD annually

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Skills and AI tools this role asks for

Data EngineeringMl PipelinesEtlDashboardingSqlAws GluePysparkKinesis

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Tell me about a project where data engineering was part of your work. What did you do?
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