Data Engineer II: Manufacturing Analytics & ML Pipelines

Amazon; Bellevue (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

PTO

401(k)

Job summary

Amazon Manufacturing Services (AMS) is hiring a data engineer to turn manufacturing data into actionable insights. You will own pipelines, warehouse, dashboards, and ML workflows turning signals from services into throughput, utilization, and quality metrics for shop floor users and AMS leadership.

You will design and operate data pipelines on AWS, model the Redshift warehouse, and build dashboards and ML models for demand forecasting and scheduling optimization.

Qualifications

• 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

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

Skills

Data engineering

ETL/ELT pipelines

SQL

AWS

Python/Java/Scala/NodeJS

Tools

Redshift

S3

AWS Glue

Kinesis

EMR

Lambda

Job description

Amazon Manufacturing Services (AMS) is hiring a data engineer to turn manufacturing data into actionable insights. You will own pipelines, warehouse, dashboards, and ML workflows turning signals from services into throughput, utilization, and quality metrics for shop floor users and AMS leadership.

You will design and operate data pipelines on AWS, model the Redshift warehouse, and build dashboards and ML models for demand forecasting and scheduling optimization.