Cloud Platform Engineer: ML Infra & Data Pipelines

Lab37; Warrendale (Allegheny County); On-site; USD 130,000 - 165,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k)

Health Savings Account (HSA)

Flexible Spending Accounts

Paid holidays

Job summary

Lab37 Robotics is seeking a Data Platform Engineer to own the data and ML platform powering our robotics fleet. You will build ETL pipelines, manage ML training infrastructure on Kubernetes, and ensure data quality and observability across the stack.

You’ll work with a small, high-impact team delivering analytics for product teams and kitchen operations. You will design the data warehouse, implement dbt transforms, and contribute to IaC and CI/CD for data workloads.

Qualifications

• Build and maintain ETL pipelines for robot telemetry data.
• Manage ML training infrastructure with Argo Workflows on Kubernetes.
• Design data quality checks and dashboards for data pipeline health.
• Own the data warehouse layer with BigQuery and dbt transforms.
• Build dashboard infrastructure (Superset, Grafana) for real-time insights.
• Collaborate with data scientists to productionize training pipelines.
• Contribute to IaC (Terraform) and CI/CD for data/ML workloads.
• Participate in on-call rotations for data reliability.

Responsibilities

• Lead ETL/ELT development across data sources and analytics.
• Oversee ML model training pipelines from data extraction to deployment.
• Maintain data quality checks and data observability dashboards.
• Optimize and manage the data warehouse with schema design and transforms.
• Provide real-time analytics via dashboards for ops and leadership.
• Collaborate with data science to automate training pipelines.

Skills

Data engineering

ML infrastructure

SQL proficiency

Python programming

Tools

Argo Workflows

Kubernetes

dbt

BigQuery

Athena

Terraform

Superset

Grafana

Docker

Job description

Lab37 Robotics is seeking a Data Platform Engineer to own the data and ML platform powering our robotics fleet. You will build ETL pipelines, manage ML training infrastructure on Kubernetes, and ensure data quality and observability across the stack.

You’ll work with a small, high-impact team delivering analytics for product teams and kitchen operations. You will design the data warehouse, implement dbt transforms, and contribute to IaC and CI/CD for data workloads.