Data Platform Engineer, Data Pipelines

FieldAI; United States; On-site; USD 120,000 - 150,000; Full time

Job summary

Field AI in Irvine, CA seeks a Data Platform Engineer, Data Pipelines to design and build the data backbone for field robotics. You will move data from robots to analytics, ML, and deployment systems, tackling intermittent connectivity and large sensor payloads while enabling scalable ingestion.

You will implement reusable ingestion SDKs, create robust integrations across edge systems and cloud storage, and ensure data quality and reliability across downstream consumers.

Qualifications

• Bachelor’s or Master’s degree in CS/Engineering or related field.
• 3–5+ years in data/backend engineering focused on pipelines and infra.
• Strong Python and SQL programming skills.
• Experience with streaming systems (Kafka/Kinesis/Pub/Sub) and schedulers (Airflow/Dagster).
• Experience with warehouse/lakehouse (BigQuery/Snowflake/Databricks/Redshift).
• Experience building integrations across APIs and services, CDC/ELT tooling.
• Experience ensuring data quality with monitoring, testing, and lineage.

Responsibilities

• Design and build the data platform, frameworks, and tooling for ingestion.
• Handle field data challenges: intermittent connectivity and large payloads.
• Develop reusable ingestion SDKs, APIs, and services for onboarding sources.
• Create integrations across robot edges, fleet tools, simulation outputs, and cloud storage.
• Integrate data with BI, ML training, labeling, and deployment pipelines.
• Build connectors and APIs (REST/gRPC, webhooks, CDC) for reliable data feeds.
• Own end-to-end integration reliability: schema contracts, versioning, retries, backfills.
• Optimize pipeline performance, scale, and cost for growing fleets.

Skills

Data engineering

Backend engineering

Python

SQL

Streaming systems

Airflow/Dagster

Cloud storage

Education

Bachelor's or Master's degree in CS/Engineering

Tools

Kafka

Kinesis

Pub/Sub

Airflow

Dagster

BigQuery

Snowflake

Databricks

Redshift

Fivetran

Airbyte

Debezium

CDC/ELT tooling

Job description

Location: Irvine, CA

About Field AI

Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact.

Learn more at https://fieldai.com.

About the Data Platform Team

Every robot we deploy generates a continuous stream of telemetry, sensor logs, and operational data from environments around the world. The Data Platform team builds the systems that capture every autonomy intervention, anomaly, and operational signal from globally deployed robots, classify them, and turn them into the ranked problem list that drives our engineering roadmap.

About the Job

As a Data Platform Engineer, Data Pipelines , you will design and build the systems and integrations that help move data reliably from robots in the field to the teams and services that depend on it — analytics, autonomy, ML training, and deployment operations. You will collaborate with cross-functional teams spanning robotics, autonomy, and deployment to build the data backbone of a field robotics company.

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

Field AI Onsite Work Philosophy

Field AI believes in-person collaboration is essential for tackling complex challenges. These are fully onsite roles based in our Irvine office, with flexible hours to support work-life balance.

We are committed to fostering a diverse and inclusive workplace and encourage candidates from all backgrounds to apply.

Why Join Field AI?

We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment. The data platform this team builds will carry every signal our robots produce — the raw material behind every autonomy improvement we ship.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

Be Part of the Next Robotics Revolution

To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!

We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.