Lab Data Systems Engineer - Pipelines & AI

Amazon Inc.; Redmond (WA); On-site; USD 129,000 - 175,000; Full time

Job summary

Amazon Leo is building a scalable lab data backbone to turn raw test data into reliable insights for battery systems. The role owns lab computing, networking, and data pipelines, ensuring secure, observable systems from local PCs to the cloud.

You will stabilize existing infrastructure, extend it with bad-data tagging, richer metadata, and dashboards; then apply AI/ML models to create predictive insights and natural-language querying for engineers.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent work experience.
• Experience in systems administration (Linux/Windows).
• Experience with automation or scripting languages like Python, Java, Perl, PHP, Ruby, Bash, Shell, or equivalent.
• Experience building and maintaining data flows and pipelines.
• Experience troubleshooting and debugging technical systems.
• Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS.
• Experience deploying and operating AI/ML models in production, or integrating them into data or user-facing applications.
• Experience with Grafana or other monitoring, BI, and visualization tools.
• Experience with networked PC administration and patching in a lab or industrial setting.
• Experience working with manufacturing test equipment and tester data.

Responsibilities

• Administer and patch networked test-floor and lab PCs (Windows and Linux).
• Build, automate, operate, and harden data pipelines to AWS S3 with observability.
• Maintain and extend data-homogenization code to a common schema.
• Improve data quality through tagging and metadata for traceability.
• Build and operate summary-metric scripts, Grafana dashboards, alerts.
• Deploy and operate AI/ML models on databases for new features.
• Specify software, networking, and security requirements for new test equipment.
• Diagnose and resolve performance, reliability, and availability issues across systems.

Skills

Python scripting

Linux

Windows

Networking

Data pipelines

Grafana

AI/ML deployment

Automation

Cloud/AWS

Security & patching

Education

Bachelor's degree in CS/CE/EE or equivalent

Tools

AWS services (EC2, Lambda, S3, DynamoDB, SQS)

Grafana

Job description

Amazon Leo is building a scalable lab data backbone to turn raw test data into reliable insights for battery systems. The role owns lab computing, networking, and data pipelines, ensuring secure, observable systems from local PCs to the cloud.

You will stabilize existing infrastructure, extend it with bad-data tagging, richer metadata, and dashboards; then apply AI/ML models to create predictive insights and natural-language querying for engineers.