Senior Production Engineer - Realtime Products

Mountain View · Texas · 5+ years experience · Remote · Posted Oct 7, 2026

At a glance

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

As a Senior Production Engineer, you will contribute to the reliability, security, and scalability of Databricks' realtime products such as Lakebase, Neon, and Model Serving.
You will build advanced monitoring and incident mitigation tooling while partnering across engineering teams to support a platform operating across AWS, Azure, and GCP.

Build advanced monitoring and detection capabilities for workload performance and customer experience.
Develop reliable, observable automation for debugging and incident mitigation.
Improve service reliability, scalability, security, and operational efficiency.
Develop safe mitigations for production issues.
Participate in a follow-the-sun on-call rotation.
Lead incident response and mitigation efforts.
Perform root-cause analysis and implement corrective actions.
Partner with Product Engineering, Security, Support, and infrastructure teams on follow-up actions.

5+ years of experience in Production Engineering, CRE, SRE, infrastructure engineering, backend software engineering, or a related field.
Experience in holistic monitoring and alerting of complex stateful systems.
Experience with PostgreSQL or related managed databases or distributed systems.
Experience in incident management and participating in on-call rotations for critical infrastructure.
Strong programming skills in Python, Go, Java, Scala, or similar.
Proficiency with infrastructure automation and Infrastructure as Code.
Experience in using AI to address production and operational challenges.
BS degree or higher in Computer Science or a related field.

Experience with AWS, Azure, or GCP.
Experience with Lakebase or Neon.
Experience with Kubernetes.
Experience with Terraform.
Experience building internal platforms, operational tooling, or developer productivity systems.