Cloud Platform - Data Engineer Warrendale, PA

Lab
37 Robotics
, a technology company focused on creating robots for direct‑to‑customer food production. Our mission is to revolutionize the food industry by delivering innovative robotic solutions that enhance efficiency, quality, and customer satisfaction.

Take ownership of the data and ML platform layer powering Lab
37's robotics fleet. This includes building ETL pipelines that turn raw robot telemetry into actionable analytics, managing the ML training infrastructure that produces the computer vision models running on robots, and ensuring the observability and reliability of the entire data stack.

Work with a small, high‑impact platform team to build the systems that every product team consumes — from data scientists training models to engineers deploying new ML models to robots in the field.

• Build and maintain ETL pipelines that ingest, validate, transform, and load robot telemetry data into Big Query for analytics and ML training
• Manage ML training infrastructure using Argo Workflows on Kubernetes, covering data extraction, model training, evaluation, and registration
• Design and maintain data quality checks and observability dashboards (the “glass panel” for data pipeline health)
• Own the data warehouse layer: schema design, incremental loading, dbt transforms, and query optimization in Big Query/Athena
• Build dashboard infrastructure (Superset, Grafana) for real‑time insights used by kitchen operations and leadership teams
• Collaborate with data scientists to product ionize model training pipelines, turning notebook experiments into reproducible, automated workflows
• Contribute to infrastructure‑as‑code (Terraform) and CI/CD pipelines for data and ML workloads
• Participate in on‑call rotations for data pipeline reliability

• 2+ years in data engineering, ML infrastructure, or analytics engineering
• Strong experience with workflow orchestration tools (Argo Workflows, Airflow, Prefect, or similar)
• Proficiency with Python data stack (pandas, SQL, dbt) and production‑quality data pipelines
• Experience with cloud data services (Big Query, Athena, S3, or GCP equivalents)
• Hands‑on building or maintaining ML training pipelines
• Familiarity with Docker, Kubernetes, and basic containerization concepts
• SQL fluency; comfortable writing complex queries and optimizing performance
• Experience with documentation tools and writing design documents
• ETL debugging, data quality frameworks, anomaly detection
• Hybrid cloud experience (AWS + GCP)
• Robotics or IoT data experience – understanding real‑world sensor data challenges
• Experience with dbt for data transformations and warehouse modeling

This role is based in our Warrendale office. We are a company driven by invention and continuous change—our office‑based teams work onsite, five days a week.

Base salary range: $130,000 – $164,500 per year.

Actual compensation will be determined individually and may vary based on experience, skills, and qualifications. In addition to base salary, you may be eligible for equity awards and an annual performance‑based bonus.

• Medical, dental, and vision insurance (multiple plans, including HSA options)
• Company‑paid life and disability insurance (short‑and long‑term)
• Voluntary insurance: accident, critical illness, hospital indemnity
• Optional supplemental life insurance for self, spouse, and children
• 401(k)
• Health Savings Account (HSA)
• Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
• Discretionary vacation days
• 8 paid holidays per year

Benefits are subject to change at the company's discretion.

Equal Employment Opportunity Statement

We do not discriminate on the basis of any protected group status under any applicable law. All qualified applicants receive equal consideration for employment opportunities.