Senior Data Engineer

Salem, OR or San Francisco Bay Area or Pittsburgh, PA

Agility Robotics is a pioneer. Our robot, Digit, is the first to be sold into workplaces across the globe. Our team is differentiated by its expertise in imagining, engineering, and delivering robots with advanced mobility, dexterity, intelligence, and efficiency -- robots specifically designed to work alongside people, in spaces built for people. Every day, we break through engineering challenges and invent new solutions and capabilities that will one day make robots commonplace and approachable.

This work is our passion and our responsibility: our mission is to make businesses more productive and people’s lives more fulfilling.

Agility Robotics is building the future of work through humanoid robots that operate in human environments. The Data Platform team builds the data infrastructure that powers everything from fleet operations and hardware reliability to business analytics and machine learning. We enable engineers across robotics, perception, and product teams to derive insight from the vast quantities of telemetry and log data generated by our robots in the field.

We are looking for a Senior Data Engineer to join our Data Platform team and help shape the foundation of data-driven operations  this role, you’ll work closely with robot software and hardware teams(among others) to design, curate, and maintain high-quality datasets that enable analytics, debugging, and fleet-scale insights.

You’ll bridge the gap between raw robot data and actionable information — working both on-robot data generation and in the cloud ingestion and processing pipelines. You’ll design transformations, author pipelines, and collaborate across teams to deliver reliable and queryable data products for hardware reliability, system health, workflow metrics, and root cause analysis.

• Collaborate with robot software and hardware teams to define, collect, and curate data needed for analytics and debugging.
• Develop and maintain ETL pipelines that transform raw robot logs and telemetry into structured datasets using Spark, Airflow (or equivalent orchestration tools), and AWS data services.
• Contribute to on-robot data production workflows to ensure high-fidelity, well-structured data capture.
• Design derived datasets and transformations across Avro, Parquet, and other sensor data formats to power fleet operations, reliability analysis, and business metrics.
• Implement data quality checks, schema evolution, and metadata management practices using our internal Data Registry and cataloging systems.
• Work closely with the ingestion and storage services that move robot data into the cloud (S3-based data lake).
• Collaborate with internal consumers — reliability, analytics, and ML teams — to design efficient data models for their workflows.
• Occasionally contribute to shared libraries or APIs in Python, Java, or C++ to support data capture and consumption.

• 5+ years of experience as a Data Engineer or similar role building and maintaining production data pipelines.
• Strong proficiency in Apache Spark or equivalent distributed data processing frameworks.
• Experience with Airflow, Dagster, Prefect, or other data orchestration systems.
• Proficiency with data formats such as Avro, Parquet, and structured/numeric datasets.
• Solid understanding of data modeling, schema evolution, and data quality best practices.
• Good intuitions of how to model datasets logically and partition them physically for optimal query performance, both for analytical query engines and for playback or root-cause-analysis(e.g. ReRun, Foxglove etc)
• Strong programming skills in Python, Java and/or Scala.
• Experience with AWS data stack (S3, Glue, Athena, EMR, etc.) or similar cloud infrastructure.
• Experience working with vision data pipelines(e.g. Images, video, depth) and building derived datasets from them.
• Comfort working cross-functionally with software, hardware, and analytics teams in a fast-paced environment

• Experience with robotics vision data (RGB, depth, point clouds, or perception outputs) and how to process, store, and query them efficiently.
• Fa…