Job Description

The role

As a Lead Data Engineer at Miso Robotics, you will design, build, and operate the data infrastructure that supports perception, autonomy, and product analytics for kitchen automation systems, working closely with machine learning and software engineering teams to ensure high-quality, reliable data flows from deployed robots to training, evaluation, and production environments. You will own end-to-end data pipelines for sensor data (including cameras), telemetry, diagnostics, and performance data, leveraging AWS and GCP cloud environments and SQL-based data platforms to enable scalable ingestion, storage, analysis, and reporting. You will partner with ML engineers to support model training, validation, and monitoring, and collaborate with software teams to integrate data capture, logging, and feedback loops into production kitchen deployments. As a technical leader, you will establish data standards, ensure data quality and governance, optimize performance and cost, and translate product, operational, and reliability needs into robust, production-ready data systems that accelerate iteration and improve automation performance in real-world kitchens.

What You’ll Do

• Develop scalable data pipelines for sensor data, telemetry, diags, &performance metrics
• Build cloud data infrastructure using AWS and GCP for analytics and ML workloads
• Develop and optimize SQL data models and queries for reporting and analysis
• Partner with ML engineers to support dataset generation, training, validation, and monitoring
• Collaborate with software teams to integrate data capture and logging into production robots
• Define data quality checks, validation, and governance standards
• Enable system diagnostics and health monitoring through metrics, dashboards, and alerts
• Optimize data pipelines for reliability, performance, and cost
• Provide curated datasets and tools to support experimentation and analysis
• Lead data architecture decisions and mentor engineers across teams

Requirements

• BS Computer Science
• 5+ years of relevant industry experience; many releases of production quality deployments
• Data pipeline design and orchestration
• Cloud data platforms on AWS and GCP
• SQL and data modeling for analytics
• Streaming and batch data processing
• Sensor, telemetry, and log data handling
• ML data support and dataset management
• Data quality, validation, and governance
• Monitoring, metrics, and diagnostics systems
• Performance and cost optimization
• Linux-based data engineering environments
• Excellent written and verbal interpersonal skills
• Attention to detail, analytical skills, and ability to learn / adapt quickly
• Collaborative team player with a drive to take initiative and ownership