Data Engineer II, Amazon Manufacturing Services (AMS)
About The Position
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.
Requirements
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Nice To Haves
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Experience working on and delivering end to end projects independently
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
Benefits
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
- sign-on payments
- restricted stock units (RSUs)
- 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
- parental leave
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
