Senior Data Engineer, Fleet Data Analytics (Remote)

Agility Robotics; Fremont (CA); Remote; USD 175,000 - 274,000; Full time

Benefits offered by this job

401(k) Plan

Equity

Medical, dental, vision insurance

Unlimited PTO

Holidays

Relocation assistance

Annual discretionary bonus

Job summary

Agility Robotics is seeking a Senior Data Engineer to join our Data Platform team. You will design, curate, and maintain high-quality datasets for analytics, debugging, and fleet-scale insights across robotics and operations.

You’ll bridge raw robot data and actionable information, building cloud ingestion pipelines and on-robot data generation to support reliability, system health, and ML workflows. Collaborate with software, hardware, and analytics teams in a fast-paced environment.

Qualifications

• Minimum 5 years as Data Engineer or similar role.
• Proficient in Spark and Python/Java/Scala.
• Experience with ETL pipelines and data warehousing best practices.

Responsibilities

• Design, curate, and maintain datasets enabling analytics, debugging, and fleet-scale insights.
• Develop and maintain ETL pipelines using Spark, Airflow, and AWS data services.
• Own gold-layer datasets with SLAs, documentation, and monitoring.
• Implement data quality checks and metadata management.
• Collaborate with reliability, analytics, and ML teams to model data.
• Contribute to shared libraries or APIs in Python/Java/C++.

Skills

5+ years experience

Apache Spark

Python

Java

SQL / Data Modeling

Airflow

Dagster / Prefect

Parquet/Avro

Iceberg/Delta Lake

Cloud AWS data services

Tools

Apache Spark

Airflow

Dagster

Prefect

Iceberg

Delta Lake

Python

Java

C++

Job description

Agility Robotics is seeking a Senior Data Engineer to join our Data Platform team. You will design, curate, and maintain high-quality datasets for analytics, debugging, and fleet-scale insights across robotics and operations.

You’ll bridge raw robot data and actionable information, building cloud ingestion pipelines and on-robot data generation to support reliability, system health, and ML workflows. Collaborate with software, hardware, and analytics teams in a fast-paced environment.