Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Data Platform Engineer, Autonomy Analytics
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full time
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and build the data platform, frameworks, and developer tooling for ingestion
Handle intermittent connectivity, large sensor payloads, edge-to-cloud sync, and offline backfill
Build reusable ingestion SDKs, APIs, and services for onboarding new robotics data sources
Integrate the platform with BI, ML training, labeling, and issue tracking systems
Own integration reliability: schema contracts, versioning, retries, backfills, and monitoring
From the employer’s posting
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.
Integrate the platform with downstream consumers: BI tools, ML training and evaluation pipelines, labeling systems, and issue tracking.
Own integration reliability end to end: schema contracts, versioning, retries, backfills, and monitoring.
Education & alternatives
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.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 123 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 11, 2026123 days ago
- Recorded sightings
- 100
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 123
Up longer than most. Similar jobs usually come down between day 6 and day 55.
Well past Field-Ai’s usual: its jobs come down by about day 27.
From 13,175 similar postings that came down, and 5 of Field-Ai’s. Coming down is not always a hire.
Field-Ai is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- C++
- Java
- Python
- Scala
- SQL
- Airbyte
- BigQuery
- Databricks
- Fivetran
- Kafka
- Redshift
- Snowflake
- Airflow
- Dagster
Where the posting names them
- 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.
- 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).
- 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.
Your next step
Complete your application on jobs.lever.co. The employer’s form will show what is required.
Applying through Lever
- No account needed: one form, and Lever reads your resume into the profile recruiters search.
Already applied? Track this application
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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.
Employment type
Full time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Irvine, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.