Modelyst

Role Description 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. - The system has been designed; what's needed is an engineer who can implement it cleanly, get it running in the customer's AWS environment, prove it out at MVP scope, and then run it as it grows. - 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. 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. Qualifications - 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. Preferred Experience - 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. Location - Remote within the United States. - Must be authorized to work in the U.S. without employer sponsorship. - Collaboration with Japan-based teams is common; Pacific or Mountain time preferred. - Occasional travel to Japan may be available. Benefits - Medical, dental, and vision insurance. - 401(k).