Data Engineer
New York, NY · New York City, New York, United States
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering › Cloud Infra — team source
Department: Engineering › Cloud Infra
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require visa sponsorship to work in the United States?
From the employer’s application form
What you’ll work on
Full postingDesign, build, and maintain scalable data pipelines and ingestion workflows
Define data quality standards, SLOs, and validation frameworks
Expand and own monitoring and alerting coverage for data issues
Optimize existing pipelines for performance and cost as data grows
Set best practices for data modeling, partitioning, and compute use
From the employer’s posting
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
Expand and own our monitoring and alerting coverage
Continuously optimize existing pipelines for performance and cost efficiency as data volumes scale
Drive best practices around data modeling, partitioning, and compute resource utilization
What you’ll bring
All qualificationsPreferred experience
- 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
Qualification wording
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
Tools in this posting
- SQL
- BigQuery
- Databricks
- Prefect
- Snowflake
- Spark
- Airflow
Source — Tool mentions in context
- 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)
Preferred Qualifications - Hands-on experience with Databricks and Spark - Experience with streaming or near-real-time ingestion patterns
- 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
Posting record
Report an errorOpen 4 monthsWe first saw this posting 132 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
- Jun 19, 2026 · 132 days ago
- Recorded sightings
- 90
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Jun 17, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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 more of the critical infrastructure our society needs.
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 South, Midwest, and Mid-Atlantic
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.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York City, New York, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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