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Salary: USD 130,000 - 164,500 / annual
Lab37 Robotics is building robotic solutions for direct-to-customer food production, revolutionizing the food industry through innovative technology. This Data Engineer role owns the data and ML platform layer powering Lab37's robotics fleet, working with a small, high-impact platform team that serves data scientists, operations teams, and field engineers.
Key responsibilities include building and maintaining ETL pipelines that ingest robot telemetry into BigQuery for analytics and ML training; managing ML training infrastructure using Argo Workflows on Kubernetes; designing data quality checks and observability dashboards; owning the data warehouse layer with schema design, dbt transforms, and query optimization; building dashboard infrastructure in Superset and Grafana for operations and leadership insights; productionizing model training pipelines from notebook experiments to automated workflows; contributing to infrastructure-as-code with Terraform; and participating in on-call rotations for pipeline reliability.
Required qualifications: 2+ years in data engineering, ML infrastructure, or analytics engineering; strong experience with workflow orchestration (Argo Workflows, Airflow, Prefect); Python data stack proficiency (pandas, SQL, dbt); cloud data services experience (BigQuery, Athena, S3); ML training pipeline building experience; Docker and Kubernetes basics; SQL fluency; and documentation skills.
Desirable skills include ETL debugging and data quality frameworks, hybrid cloud environments (AWS + GCP), robotics or IoT data experience, and dbt expertise.
The role is based in Pittsburgh with five-day-per-week onsite work. Base salary ranges from $130,000–$164,500 annually, with equity awards and performance-based bonuses. Benefits include medical, dental, vision, life and disability insurance, and voluntary coverage options.
