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Open nowPosted 80 days ago

Data Platform Engineer, Autonomy Analytics

FieldAI95 open roles

Where
Irvine, CA
Work mode
On site
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Your applicationOpen nowData Platform Engineer, Autonomy AnalyticsFieldAI · Irvine, CA

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.4%1 day
  2. 3.5%3 days
  3. 7.7%7 days
  4. 13.4%14 days
  5. 34.5%30 days
This job: posted 80 days ago

The posting

What You'll Get To Do

  • Design and build the data platform, frameworks, and developer tooling that power ingestion across Field AI.
  • Handle the realities of field data: intermittent connectivity, large sensor payloads (LiDAR, camera, IMU), edge-to-cloud synchronization, and backfill from offline deployments.
  • Develop reusable ingestion SDKs, APIs, and services that enable teams to onboard new robotics data sources with minimal custom code.
  • Build and maintain integrations across heterogeneous sources: robot/edge systems, fleet management and deployment tooling, simulation outputs, and cloud object storage.
  • Integrate the platform with downstream consumers: BI tools, ML training and evaluation pipelines, labeling systems, and issue tracking.
  • Develop connectors and APIs (REST/gRPC, webhooks, CDC) so internal teams can feed data in and consume curated datasets reliably.
  • Own integration reliability end to end: schema contracts, versioning, retries, backfills, and monitoring.
  • Optimize pipeline performance, scalability, and cost across growing fleet deployments.

What You Have

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
  • 3–5+ years of experience in data engineering or backend engineering focused on pipelines and infrastructure.
  • Strong programming skills in Python and SQL (C++, Scala, or Java a plus).
  • Production experience with streaming systems (Kafka, Kinesis, Pub/Sub) and orchestration tools such as Airflow or Dagster.
  • Experience with a modern warehouse or lakehouse (BigQuery, Snowflake, Databricks, Redshift) and cloud object storage at scale.
  • Experience building integrations across systems: third-party APIs, internal services, and CDC/ELT tooling (Fivetran, Airbyte, Debezium, or custom connectors).
  • Experience building for data quality: testing, monitoring, lineage, and incident response.
  • Strong problem-solving skills and ability to work in interdisciplinary teams.

The Extras That Set You Apart

  • Experience with robotics, autonomy, automotive, or other telemetry-heavy operational data (bag files, fleet logs, time-series sensor data).
  • Familiarity with robotics middleware and log formats such as ROS/ROS2, MCAP, or rosbag.
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