FieldAI
Data Platform Engineer, Data Pipelines
Irvine, CA
Sponsorship not specifiedDetected 11 days ago
PythonJavaC++ScalaSQLBigQuerySnowflakeRedshiftDatabricksPlatform EngineeringRESTgRPCKafkaMachine LearningAirflowdbtData EngineeringNLPRoboticsSensorsResearchCollaborationProblem Solving
About the role
- About Field AI Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing.
- Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact.
Responsibilities
- Design and build the data platform, frameworks, and developer tooling that power ingestion across Field AI.
- 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.
- 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.
- 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.
Requirements
- Strong problem-solving skills and ability to work in interdisciplinary teams.
- 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.
Nice to 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.
Skills
- robot/edge systems, fleet management and deployment tooling, simulation outputs, and cloud object storage.
Company info
- We are committed to fostering a diverse and inclusive workplace and encourage candidates from all backgrounds to apply.
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This listing is sourced directly from FieldAI's careers page and normalized into a canonical job model.