Data Platform Engineer, Data Pipelines

Field AI is transforming how robots interact with the real world by building risk-aware, reliable, and field-ready AI systems for robotics. The Data Platform Engineer will design and build reliable data pipelines, integrations, APIs, and developer tooling that move telemetry and operational data from deployed robots to analytics, autonomy, machine learning, and deployment teams.

Artificial Intelligence (AI)

• Transportation
• Enterprise Software
• Robotics
• Autonomous Vehicles
• Robotic Process Automation (RPA)
• Insider Connection @FieldAI
• 2 email credits available today
• Beyond your network
• Mario Portugal & 1 connections
• From your previous company
• Karan Owalekar

Responsibilities

• 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

Preferred

• 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
• Experience with edge computing or intermittently connected data collection
• Experience with dbt or similar transformation frameworks

Benefits

• Fully onsite role based in the Irvine office
• Flexible hours to support work-life balance
• Opportunity to work with a world-class team
• Fun, close-knit team
• FieldAI is building general robot intelligence for the physical world.
• Irvine, California, USA
• https://www.fieldai.com
• Distribution of Different Job Fields Receiving Sponsorship
• Represents job field similar to this job
• Engineering and Development
• Trends of Total Sponsorships
• *2026
• (37)
• 2025
• (9)
• Growth Stage
• Total Funding
• $405M
• Key Investors
• Hyundai Motor Group
• Bezos Expeditions,Prysm Capital,Temasek
• 2026-02-22
• Corporate Round
• 2025-08-20
• Series Unknown· $91M
• Series A· $314M
• Leadership Team
• Ali Agha
• Founder and CEO
• Recent News

Qualifications

• 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
• These are fully onsite roles based in our Irvine office, with flexible hours to support work-life balance
• 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
• Experience with edge computing or intermittently connected data collection
• Experience with dbt or similar transformation frameworks

Required skills

• Python, SQL, Apache Kafka, Amazon Kinesis, Google Cloud Pub/Sub, Apache Airflow, Dagster, BigQuery, Snowflake, Databricks, Amazon Redshift, REST/gRPC APIs

Preferred skills

• Experience with dbt or similar transformation frameworks

Experience

• 3+ years