Sr. Staff Technical Program Manager - Reliability

Databricks Databricks · Data AI · San Francisco, CA · Engineering - Pipeline

Databricks is seeking a Senior Staff Technical Program Manager for Reliability to lead strategy and execution of critical reliability initiatives across infrastructure and product engineering. This role involves partnering with senior engineering leaders to define reliability strategy, set long-term goals, and execute multi-quarter programs to enhance the reliability, performance, and operational excellence of their multi-cloud infrastructure. The ideal candidate will have deep understanding of large-scale distributed systems, cloud infrastructure, and engineering principles, with a proven track record in leading reliability programs at scale.

What you'd actually do

  1. Partner with senior engineering leadership to define the long-term Reliability roadmap, influence technical direction, and ensure alignment across teams.
  2. Own program execution end-to-end: planning, risk management, dependency mapping, trade-off decisions, status reporting, and delivery.
  3. Using your background in infrastructure, distributed systems, or SRE to help teams make sound design and prioritization decisions.
  4. Drive adoption of reliability best practices across engineering teams - including error budgets, incident reviews, design-for-resilience patterns, and operational readiness.
  5. Define and implement program governance, repeatable processes, metrics, and documentation to scale reliability efforts across teams.

Skills

Required

  • 10+ years of experience managing and delivering large-scale technical programs in cloud infrastructure, distributed systems, SRE, or platform engineering environments.
  • Experience developing infrastructure at two or more hyperscale cloud providers (e.g., AWS, Azure, GCP), with knowledge of cloud primitives, multi-AZ/region architecture, and control plane/data plane patterns.
  • Demonstrated success leading Reliability Programs at scale - including availability, failover, operational excellence, incident reduction, or dependency hardening.
  • Strong understanding of infrastructure, distributed systems, or SRE practices; previous engineering or SRE experience is highly preferred.
  • Experience partnering directly with senior engineering leadership to define strategy and drive large, multi-team initiatives.
  • Ability to translate ambiguous goals into actionable program plans with clear milestones, KPIs, and success metrics.
  • Demonstrated ability to manage complex cross-organizational dependencies, technical risks, and multi-quarter timelines.
  • Experience delivering programs across multiple clouds and/or large-scale cloud-native services.
  • Experience building and scaling engineering processes, operational frameworks, and stakeholder alignment mechanisms.

Nice to have

  • Background in distributed systems engineering, SRE, platform infrastructure, or cloud services.
  • Experience with large-scale compute fleets, container orchestration, autoscaling, or control-plane architecture.
  • Familiarity with reliability methodologies such as SLOs, error budgets, chaos engineering, failure mode analysis, and incident management frameworks.
  • Expertise using Jira or equivalent tools for program tracking and execution.
  • Bachelor’s degree in Computer Science, Engineering, or related technical field; advanced degree preferred.

What the JD emphasized

  • 10+ years of experience managing and delivering large-scale technical programs in cloud infrastructure, distributed systems, SRE, or platform engineering environments.
  • Demonstrated success leading Reliability Programs at scale - including availability, failover, operational excellence, incident reduction, or dependency hardening.
  • Experience partnering directly with senior engineering leadership to define strategy and drive large, multi-team initiatives.
  • Demonstrated ability to manage complex cross-organizational dependencies, technical risks, and multi-quarter timelines.
  • Experience building and scaling engineering processes, operational frameworks, and stakeholder alignment mechanisms.