Cloud Platform - Data Engineer

The Consensus; Pittsburgh (Allegheny County); On-site; USD 130,000 - 165,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Company-paid life and disability

401(k)

Health Savings Account (HSA)

Flexible Spending Accounts

Discretionary vacation days

8 paid holidays

Job summary

Lab37 Robotics in Pittsburgh is seeking a data/ML platform lead to own the data stack powering our robotics fleet. You will build ETL pipelines, manage ML training infra, and ensure observability across the data stack to deliver reliable analytics for product teams and kitchen operations.

You will collaborate with data scientists and engineers, contribute to IaC and CI/CD, and help scale our hybrid cloud data estate.

Qualifications

• 2+ years in data engineering, ML infra, or analytics engineering.
• Proficient with workflow tools such as Argo Workflows, Airflow, or similar.
• Strong Python data stack (pandas, SQL, dbt) for building production pipelines.
• Experience with cloud data services (BigQuery, Athena, S3) and hybrid clouds.
• Experience building ML training pipelines and model deployment.
• Familiarity with Kubernetes and containerization concepts.
• SQL fluency and performance-oriented data querying.
• Ability to document designs and write technical docs.
• Robotics or IoT data experience is a plus.

Responsibilities

• Own data warehouse layer: schema design, incremental loading, dbt transforms.
• Build and maintain ETL pipelines ingesting robot telemetry into BigQuery.
• Manage ML training infra using Argo Workflows on Kubernetes.
• Design observability dashboards for data quality and pipeline health.
• Develop dashboard infra (Superset, Grafana) for real-time insights.
• Collaborate with data scientists to productionize training pipelines.
• Contribute to Terraform-based IaC and CI/CD for data/ML workloads.
• Participate in on-call rotations for data pipelines.

Skills

Argo Workflows

Python data stack

SQL

dbt

BigQuery

Kubernetes

Cloud (AWS + GCP)

Robotics data

Documentation

Tools

Airflow

Superset

Job description

Lab37 Robotics , is a technology company focused on the development and deployment of robots designed specifically for direct-to-customer food production. Our mission is to revolutionize the food industry by creating innovative robotic solutions that enhance efficiency, quality, and customer satisfaction. We are passionate about pushing the boundaries of technology to deliver cutting‑edge products that meet the evolving needs of our clients.

What you'll do

Take on ownership of the data and ML platform layer that powers Lab37's robotics fleet. This spans building ETL pipelines that turn raw robot telemetry into actionable analytics, managing the ML training infrastructure that produces the computer vision models running on our 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 at Lab37 consumes — from data scientists training models, to kitchen operations teams viewing dashboards, 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 — from data extraction through 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 BigQuery/Athena query optimization
• Build dashboard infrastructure (Superset, Grafana) that kitchen operations and leadership teams rely on for real‑time insights
• Collaborate with data scientists to productionize model training pipelines — from notebook experiments to 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)
• Python data stack proficiency — pandas, SQL, dbt, and comfort writing production‑quality data pipelines
• Experience with cloud data services (BigQuery, Athena, S3, or GCP equivalents)
• Experience building or maintaining ML training pipelines (not just using them as a consumer)
• Docker containerization and Kubernetes basics
• SQL fluency — you'll write complex queries daily and care about query performance
• Familiarity with documentation tools and writing design documents
• ETL debugging, data quality frameworks, and anomaly detection
• Experience with hybrid cloud environments (AWS + GCP)
• Robotics or IoT data experience — understanding the challenges of real‑world sensor data
• Experience with dbt for data transformations and warehouse modeling
• Demand for online food delivery is growing really fast! In the last 5 years, just in the US, the overall market has expanded 10X from $10B to $100B, and could expand to $500bn- $1T by 2030.
• Changing the restaurant industry: You’ll be part of a team that helps restaurants succeed in online food delivery.
• Collaborative environment: You will receive support and guidance from experienced colleagues and managers, helping you to learn, grow and achieve your goals, and you’ll work closely with other teams to ensure our customer’s success.

What else you need to know

This role is based in our Pittsburgh office. As a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That’s why all of our office-based teams work onsite, five days a week.

The base salary range for this role is $130,000 - $164,500 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also 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, incl. 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.

As set forth in ATOMS Careers page’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.