Cloud Platform - Data Engineer Pittsburgh, PA

Lab37; Pennsylvania; On-site; USD 130,000 - 164,500; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Health Savings Account (HSA)

401(k)

Job summary

Lab37 Robotics is seeking a data/ML infrastructure engineer to own the data and ML platform powering our robotics fleet. You will build ETL pipelines from robot telemetry to analytics, manage ML training infra on Kubernetes, and ensure observability of the entire data stack.

You will work with a small platform team to deliver systems used by data scientists and engineers, collaborating on model training pipelines, dashboards, and CI/CD for data workloads.

Qualifications

• 2+ years in data engineering or ML infrastructure.
• Experience with workflow orchestration tools such as Argo, Airflow or Prefect.
• Proficiency with Python data stack (pandas, SQL) and production‑quality data pipelines.
• Experience with cloud data services (BigQuery, Athena, S3) or equivalents.
• Hands‑on building or maintaining ML training pipelines.

Responsibilities

• Build and maintain ETL pipelines ingesting robot telemetry into BigQuery 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 for data pipeline health.
• Own the data warehouse layer: schema design, incremental loading, dbt transforms, and query optimization in BigQuery/Athena.
• Build dashboard infrastructure (Superset, Grafana) for real‑time insights used by kitchen operations and leadership.
• Collaborate with data scientists to productionize model training pipelines as reproducible 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.

Skills

Argo Workflows

Airflow

Python

SQL

dbt

Kubernetes

Docker

BigQuery

Data Pipelines

AWS & GCP

Robotics data

Tools

dbt

BigQuery

Athena

Grafana

Superset

Terraform

Kubernetes

Job description

Lab37 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.

What you'll do

Take ownership of the data and ML platform layer powering Lab37'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.

Responsibilities

• Build and maintain ETL pipelines that ingest, validate, transform, and load robot telemetry data into BigQuery 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 BigQuery/Athena
• Build dashboard infrastructure (Superset, Grafana) for real‑time insights used by kitchen operations and leadership teams
• Collaborate with data scientists to productionize 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

What we're looking for

• 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 (BigQuery, 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

What else you need to know

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.

Benefits Summary (USA Full‑Time Exempt Employees)

• 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.