Team Lead - Platform Monitoring Engineer
Databricks (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 40–65 LPA
Posted 2h ago
Reach people at Databricks
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Databricks you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead platform incident investigations and coordinate cross-functional teams to minimize customer impact through rapid detection, mitigation, and resolution.
- Design and implement customer-focused alerting pipelines and observability workflows to expand coverage and reduce mean time to detection.
- Build automation tools and monitoring patterns to close reliability gaps and directly improve customer experience; structure and participate in on-call rotations.
Minimum Requirements
- Minimum 6 years experience in SRE, DevOps, CRE, Production Engineering or similar roles.
- At least 2 years of engineering leadership experience with mentorship and coaching responsibilities.
- Production-level experience with one major cloud provider (AWS, Azure, GCP) and container/orchestration technologies (Docker, Kubernetes).
- Proficiency with monitoring/logging/alerting tools (ELK, Prometheus, Grafana, PagerDuty), Python or similar for automation, and experience in incident lifecycle ownership.
Ideal Candidate Profile
- Experienced technical leader blending platform reliability expertise with people leadership and cross-team collaboration skills.
- Strong background in architecting complex monitoring and alerting solutions that correlate metrics, logs, and traces for customer reliability.
- Comfortable operating in high-severity incident environments and driving root cause analysis for systemic improvements.