
1001 - 5000 employees
Founded 2013
🤖 Artificial Intelligence
🏢 Enterprise
☁️ SaaS
💰 $1.6G Series H on 2021-08
Artificial Intelligence • Enterprise • SaaS
Databricks is a data and AI company that provides a unified platform for data engineering, machine learning, and analytics. It focuses on optimizing big data processing and helps organizations leverage Apache Spark to deliver deeper insights and powerful data-driven applications. Databricks also offers robust tools and seamless integration for machine learning operations.
🔥 0 minutes ago
🏄 California – Remote
💵 $115.7k - $198.9k / year
⏰ Full Time
🟠 Senior
👷🏻♀️ Engineer
🦅 H1B Visa Sponsor
👻 Ghost score 1%
Where this job comes from
Posted on Databricks's careers page, not through a job board
First seen by Remote Rocketship 0 minutes ago

1001 - 5000 employees
Founded 2013
🤖 Artificial Intelligence
🏢 Enterprise
☁️ SaaS
💰 $1.6G Series H on 2021-08
Artificial Intelligence • Enterprise • SaaS
Databricks is a data and AI company that provides a unified platform for data engineering, machine learning, and analytics. It focuses on optimizing big data processing and helps organizations leverage Apache Spark to deliver deeper insights and powerful data-driven applications. Databricks also offers robust tools and seamless integration for machine learning operations.
• Lead platform incident investigations and coordinate cross-functional teams through detection, mitigation, and resolution • Conduct post-incident root cause analyses across infrastructure, services, and cloud providers • Design and implement customer-focused alerting pipelines and end-to-end observability workflows • Build automation tools and reusable monitoring patterns • Resolve reliability gaps affecting customer experience • Provide mentorship to junior engineers on observability patterns, alert design, and service health metrics • Participate in the on-call rotation
• Minimum of 6 years of experience as an SRE, DevOps Engineer, Production Engineer, or similar role • Production-level experience with at least one major cloud provider (AWS, Azure, GCP) • Proficiency in Docker and Kubernetes • Hands-on experience with monitoring, logging, and alerting tools such as ELK, Prometheus, Grafana, and PagerDuty • Ability to architect monitoring solutions correlating metrics, logs, and traces • Strong proficiency in Python or similar languages • Ability to build production-quality automation tools • Experience owning critical phases of the incident lifecycle from detection through resolution and post-mortem analysis in demanding production environments • BS, Master's, or PhD in Computer Science, Computer Engineering, or a related Engineering field • Participation in an on-call rotation
• Eligibility for annual performance bonus • Equity • Comprehensive benefits and perks, with details varying by region
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