Data Platform Engineer

Join the Team Bringing Autonomy to the Built World

At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs.

In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic

In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.

This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.

The Role

You’ll own the data platform the rest of Bedrock builds on: the systems that move, store, and serve data from compute on our machines in the field to high-throughput, low-latency services in the cloud. This is an infrastructure role, not a pipeline-maintenance one. You’ll design the foundations that autonomy, ML, simulation, and operations teams use to work with data at fleet scale. As the fleet and the number of users grow, you’ll make sure the platform scales, stays reliable, and stays cost-efficient.

What You’ll Do

• Design and own the architecture of our data platform, from edge ingestion through lakehouse storage, compute, and serving
• Build systems that get high-volume sensor and log data off machines in the field reliably, including over limited or intermittent connectivity
• Build and run low-latency, high-throughput data services that internal teams depend on
• Set platform standards for reliability, SLOs, observability, and incident response
• Keep performance and cost in check as data volume and compute usage grow
• Build the self-serve tooling and abstractions that let other engineers ship data workflows without going through you
• Own data governance, access control, and lineage at the platform level

What We’re Looking for

• 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
• A strong software engineering background: you write production code (Python, Go, Rust, Scala, or similar), not just SQL and configs
• Experience running infrastructure in the cloud with modern tooling (Kubernetes, infra-as-code, CI/CD)
• A track record of owning reliability: monitoring, alerting, on-call, and SLOs for systems other teams depend on
• Good judgment about build-vs-buy tradeoffs and platform design that has to hold up for years

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