Data Engineer
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- Work arrangement
- hybrid
- Employment
- FullTime
- Stated compensation
- Not specified
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Requirements
2 with evidence7 unclear or unstated- Remote policy
- hybrid
“Provider workplace type: hybrid”
From employer posting metadata - Minimum experience (years)
- 5
“5+ years of experience in data engineering, with a strong track record in large-scale data lake or data warehouse environments”
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- FullTime
8 fields not stated in this posting
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Original job description
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Join the team bringing autonomy to the built world
At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver them more predictably.
In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the West, South, and Midwest.
In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.
This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.
The Role
Our Data Platform is growing fast - more users, more data sources, more pipelines - and the expectations that come with that growth are rising accordingly. We need a Senior Data Engineer who can work across the stack: tighten up our ingestion pipelines, write new ETL pipelines wherever needed, build out monitoring and alerting where we have blind spots, and help internal teams build their own data infrastructure “the right way”. You'll spend real time in the weeds - writing and debugging pipelines, optimizing queries, reviewing what others have built - and you should be comfortable with that.
This is a high-impact role. Our data is increasingly tied to the experiences we deliver to customers, which means data quality, accuracy, and observability are no longer just engineering concerns - they directly affect trust. You'll be at the center of that challenge.
What you’ll do
You will design, build, and maintain robust, scalable data pipelines and ingestion workflows across a growing Data Lake;
Define and enforce data quality standards, SLOs, and validation frameworks to ensure accuracy and reliability of critical data assets;
Continuously optimize existing pipelines for performance and cost efficiency as data volumes scale;
Expand and own our monitoring and alerting coverage — surfacing data issues before they become customer-facing problems;
Drive best practices around data modeling, partitioning, and compute resource utilization;
Also, you get to drive 100,000 lb excavators.
What we’re looking for
5+ years of experience in data engineering, with a strong track record in large-scale data lake or data warehouse environments
5+ years of experience working with SQL and distributed query engines (e.g. Spark, BigQuery, Snowflake, or similar)
Deep proficiency with pipeline orchestration tools (e.g. Airflow, Prefect, or equivalent) and transformation frameworks (e.g. Spark)
Experience designing and implementing data quality frameworks - validation, anomaly detection, lineage tracking
Familiarity with observability tooling for data systems: monitoring, alerting, and incident response for data pipelines
Experience enabling non-engineering stakeholders to self-serve on data infrastructure, whether through documentation, tooling, or hands-on enablement
Preferred Qualifications
Hands-on experience with Databricks and Spark
Experience with streaming or near-real-time ingestion patterns
Familiarity with data governance and access control at scale
Background working on customer-facing data products or external SLAs
Bedrock Robotics is an Equal Opportunity Employer
We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations
We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.
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