Data Platform Engineer

The role

You will own the data platform architecture from edge ingestion to cloud services. You will design foundations for autonomy, ML, simulation, and operations teams to work with data at fleet scale.

What you will do

• Design and own the architecture of the data platform
• Build systems to get high-volume sensor and log data off machines in the field
• Build and run low-latency, high-throughput data services
• Set platform standards for reliability, SLOs, observability, and incident response
• Keep performance and cost in check as data volume and compute usage grow
• Build self-serve tooling and abstractions for other engineers
• Own data governance, access control, and lineage at the platform level

Required qualifications

• 5+ years building data infrastructure or distributed systems in production
• Deep experience with large-scale storage and compute: data lakes or lakehouses, Spark or similar distributed engines, partitioning and file formats
• Strong software engineering background writing production code (Python, Go, Rust, Scala, or similar)
• Experience running infrastructure in the cloud with modern tooling (Kubernetes, infra-as-code, CI/CD)
• Track record of owning reliability: monitoring, alerting, on-call, and SLOs
• Good judgment about build-vs-buy tradeoffs and platform design

Nice to have

• Hands-on experience with Databricks
• Streaming or near-real-time ingestion (Kafka, Kinesis, Flink, or similar)
• Experience with robotics, autonomous vehicles, IoT, or other edge-to-cloud data systems
• Large-scale multimodal or sensor data (camera, lidar, telemetry)
• Orchestration tools like Airflow or Prefect

About the company

Bedrock retrofits heavy equipment like excavators to perform fully autonomous work on live commercial job sites. The team includes veterans from Waymo, Segment, and Uber Freight.