Senior Production Engineer - Realtime Products
Databricks9 hours ago
Responsibilities
- Build advanced monitoring and detection capabilities for workload performance, system health, and customer experience.
- Develop observable automation for debugging and incident mitigation.
- Improve service reliability, scalability, security, and operational efficiency.
- Participate in a follow-the-sun on-call rotation and lead incident response and mitigation.
- Perform root-cause analysis and implement lasting corrective actions for production issues.
- Partner with Product Engineering, Security, Support, infrastructure teams, and customer infrastructure teams.
- Build durable solutions for a platform operating across AWS, Azure, and GCP.
Requirements
- 5+ years of experience in Production Engineering, Customer Reliability Engineering, Site Reliability Engineering, infrastructure engineering, backend software engineering, or a related field.
- Experience monitoring and alerting complex stateful systems using workload alerting, anomaly detection, and probing.
- Experience with PostgreSQL or related managed databases or distributed systems.
- Experience with incident management and on-call rotations for critical infrastructure.
- Strong programming skills in one or more languages such as Python, Go, Java, Scala, or similar.
- Proficiency with infrastructure automation and Infrastructure as Code.
- Ability to work across system boundaries and collaborate during complex incidents and with customer infrastructure teams.
- Experience using AI to address production and operational challenges.
- BS degree or higher in Computer Science or a related field.
- Bonus: experience with AWS, Azure, GCP, Lakebase, Neon, Kubernetes, Terraform, internal platforms, operational tooling, or developer productivity systems.
Benefits
- Comprehensive benefits and perks are offered, with details varying by region.
Tech Stack
Categories
Site Reliability
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.