Senior Data Engineer

Modelyst • Sacramento, CA

4d • $130,000 - $170,000 • Remote

About The Position

Modelyst is a three-person engineering firm building production data and machine learning infrastructure for manufacturing and research environments. Our systems support real-world operations and are designed to be reliable, maintainable, and cost-efficient. We partner directly with academic labs, national laboratories, and enterprise R&D organizations, and maintain long-term engagements in the industrial sector.

The Role
We are hiring a Senior Data Engineer to take a designed-but-not-yet-deployed AWS data platform from architecture to a working MVP at a customer site in Japan and then own its operation from there. You will work on implementing the system, getting it running in the customer's AWS environment, and proving it out at MVP scope and beyond. You'll be the person accountable for the platform from "deployed" through "running reliably in production" through "evolving as the workload grows."

Initial work is focused on standing up infrastructure, implementing data pipelines and backend services, validating the system end-to-end against real operational data, and bringing it live for an MVP deployment. After launch, the role shifts to operating and extending the platform as the engagement matures.

This role is best suited for engineers who take pride in shipping into production environments where reliability matters and want to own a system over a multi-year arc rather than handing it off. You will focus on this single engagement rather than being fragmented across multiple projects.

Requirements

• Senior-level experience shipping production backend or data services in Python. You have built systems other people depend on.
• Production AWS architecture experience, including event-driven services such as SQS, SNS, EventBridge, Step Functions, and Lambda.
• Infrastructure-as-code with Terraform (Terragrunt is our standard). You've stood up and managed cloud infrastructure end-to-end.
• You've operated systems in production — incident response, performance, capacity, cost — and been the person accountable when something breaks.

Nice To Haves

• Time-series or high-throughput data environments
• Industrial, manufacturing, robotics, or IoT systems
• ML infrastructure or MLOps tooling
• Large-scale data processing frameworks (e.g., Spark, Databricks)
• Japanese language ability is helpful but not required

Responsibilities

• Implement the designed data pipelines and backend services in Python on AWS
• Design and manage AWS infrastructure using Terraform and Terragrunt
• Deploy the platform end-to-end into the customer's AWS environment and bring it live for an MVP launch, validating against real operational data
• Build out the CI/CD, observability, and runbooks needed to operate the platform reliably
• Own the platform after launch — incident response, performance, capacity, and cost
• Lead the platform's design evolution from MVP through later production stages, making the data model, scaling, and reliability decisions informed by running it yourself

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed