Databricks
Senior Production Engineer - Realtime Products
$164K–$226K
Mountain View, California · Senior · Full-time · Posted Oct 7, 2026
- Experience
- 5+ years in Production Engineering, Customer Reliability Engineering (CRE), Site Reliability Engineering (SRE), infrastructure engineering, backend software engineering, or a related field.
- Education
- BS degree (or higher) in Computer Science or a related field.
- Visa sponsorship
- If access to export-controlled technology or source code is required, the employer may choose whether to apply for a U.S. government license and may decline to proceed with an applicant on that basis alone.
About the job
Build monitoring, incident-mitigation, and reliability improvements for Databricks’ realtime products, and lead production incident response across a multi-cloud platform.
What you'll do
- Develop monitoring, detection, debugging, and incident-mitigation tooling.
- Improve service reliability, scalability, security, and operational efficiency; perform root-cause analysis and implement corrective actions.
- Participate in a follow-the-sun on-call rotation, lead incident response, and coordinate follow-up across teams.
What they ask for
- Experience with monitoring and alerting complex stateful systems, including strategies such as workload alerting, anomaly detection, and probing.
- Experience with PostgreSQL or related managed databases or distributed systems.
- Experience managing incidents and participating in on-call rotations for critical infrastructure.
- Strong programming skills in one or more languages such as Python, Go, Java, or Scala; proficiency with infrastructure automation and Infrastructure as Code.
Nice to have
- Experience with AWS, Azure, or GCP; Lakebase or Neon.
- Experience with Kubernetes, Terraform, or building internal platforms, operational tooling, or developer productivity systems.
Pay
$164,200 — $225,700 USD (salary range; non-commissionable roles or on-target earnings for commissionable roles).
Tools
PostgreSQL, Python, Go, Java, Scala, AWS, Azure, GCP
AI focus
Use AI to address production and operational challenges.
Model-written summary · the original posting is authoritative