Data Engineer

Bedrock Robotics • New York City, NY

6d

About The Position

Join the team bringing advanced autonomy to the built world At Bedrock, we’re moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we’re deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we’re working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You’ll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can’t touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed