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About the Role

The Data Platform is rapidly expanding, requiring a Senior Data Engineer to manage ingestion and ETL pipelines, develop monitoring and alerting systems, and guide internal teams in building data infrastructure. This high-impact role focuses on ensuring data quality, accuracy, and observability, which are critical for customer trust.

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 monitoring and alerting coverage, surfacing data issues before they become customer-facing problems
• Drive best practices around data modeling, partitioning, and compute resource utilization
• Drive 100,000 lb excavators

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 through documentation, tooling, or hands-on enablement
• 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

Skills

• Data engineering
• SQL
• Spark
• BigQuery
• Snowflake
• Airflow
• Prefect
• Data quality frameworks
• Validation
• Anomaly detection
• Lineage tracking
• Observability tooling
• Monitoring
• Alerting
• Incident response for data pipelines
• Databricks
• Streaming ingestion
• Near-real-time ingestion
• Data governance
• Access control

Location

• Across the country
• SF
• NY

Experience Level

• 5+ years of experience in data engineering
• 5+ years of experience working with SQL and distributed query engines

About the Company

• Bedrock is moving AI out of the lab and into the real world.
• The 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.
• Bedrock deploys autonomous systems on heavy construction machinery across the country.
• The company accelerates project schedules of billion-dollar infrastructure projects and improves safety on job sites.
• Backed by $350M in funding.
• Bedrock is working to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.
• Employees collaborate with construction veterans and world-class engineers to solve physical-world problems.