Senior Data Engineer

🕒 May 4

🇺🇸 United States – Remote

💵 $147k - $178k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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dbt Labs

WebsiteLinkedInAll Job Openings

51 - 200 employees

dbt Labs is on a mission to empower data practitioners to create and disseminate organizational knowledge. Since pioneering the practice of analytics engineering through the creation of dbt—the open source data transformation tool made for anyone that knows SQL—we've been fortunate to watch more than 5,000 companies use dbt to build faster and more reliable analytics workflows.

📋 Description

• Own the architecture and operations of our data lakehouse, including object storage, table formats, maintenance, and query engine integrations • Build and maintain the infrastructure layer that transforms and serves data reliably at scale—from raw landing zones through to curated, queryable datasets • Partner with product engineering to establish data contracts and schema standards around event telemetry, ensuring data arrives in the lakehouse in a form that's reliable and ready for downstream use • Drive decisions on data platform architecture, tooling, and engineering best practices across storage, compute, and access layers • Enhance observability and monitoring of data infrastructure, including pipeline reliability, data freshness, and system performance • Partner cross-functionally with teams across Analytics, Infrastructure, and Product to understand data needs and deliver impactful platform solutions • Provide product feedback by dogfooding new data infrastructure and AI technology

🎯 Requirements

• Expert-level SQL and Python skills • 5+ years of experience as a data engineer, and 8+ years of total experience in software engineering (including data engineering roles) • Strong knowledge of data lakehouse architecture, including storage layer design, table formats, and compute/query engine integration • Experience defining and enforcing data contracts or schema standards in collaboration with upstream engineering teams • Hands-on experience with modern orchestration tools like Airflow, Dagster, or Prefect • Working knowledge of cloud infrastructure tooling, including Terraform, Helm, and Kubernetes • Hands-on experience running Apache Spark in production, including job tuning, cluster sizing, and managing failures at scale • A bias for action—able to stay focused and prioritize effectively in an ambiguous environment

🏖️ Benefits

• Unlimited vacation time with a culture that actively encourages time off • 401k plan with 3% guaranteed company contribution • Comprehensive healthcare coverage • Generous paid parental leave • Flexible stipends for: • Health & Wellness • Home Office Setup • Cell Phone & Internet • Learning & Development • Office Space