Cloud Platform - Data Engineer
About The Position
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. In this role, you will take 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. You will 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.
Requirements
- 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
Nice To Haves
- 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
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
Benefits
- 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.
- Pet insurance discount.
- 401(k).
- Health Savings Account (HSA)
- Flexible Spending Accounts (Healthcare, Dependent Care, Commuter)
- Discretionary vacation days
- 8 paid holidays per year
- Paid sick time
- Paid Bereavement leave
- Paid Parental Leave
- Equity awards
- Annual performance-based bonus
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
