Databricks

Databricks

Posted via Greenhouse

Sr. Staff Technical Program Manager - Reliability

Posted Aug 5, 2026

Role at a glance

Salary
$189.8K – $256.2K/yr
Location
Mountain View, California, United States San Francisco, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
10+ years of experience managing and delivering large-scale technical programs in cloud infrastructure, distributed systems, SRE, or...
Education
Bachelor’s degree in Computer Science, Engineering, or related technical field; advanced degree preferred.

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Role Summary

AI-generated

The Senior Staff Technical Program Manager for Reliability leads strategy, execution, and continuous improvement for critical reliability initiatives across Databricks’ infrastructure and product engineering teams. The role partners with engineering, SRE, security, and cloud partnership teams to improve the reliability, performance, and operational excellence of the company’s multi-cloud infrastructure.

What You'll Do

  • Define the long-term Reliability roadmap and align priorities across engineering teams.
  • Own end-to-end execution of critical reliability programs, including planning, risk management, dependency mapping, trade-off decisions,...
  • Identify process or architecture gaps and drive organizational or technical improvements with technical leaders.
  • Facilitate alignment across cross-functional teams and support technically grounded design and prioritization decisions.
  • Drive adoption of reliability practices, program governance, metrics, documentation, and operational readiness processes across...

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

Required: 10+ years managing and delivering large-scale technical programs; infrastructure experience with two or more hyperscale cloud providers; reliability program leadership; understanding of infrastructure, distributed systems, or SRE practices; senior engineering leadership partnership; program planning, dependency, risk, and multi-quarter timeline management; experience across multiple clouds and/or large-scale cloud-native services; engineering process and operational framework development.

Required

  • 10+ years of experience managing and delivering large-scale technical programs in cloud infrastructure, distributed systems, SRE, or...
  • Experience developing infrastructure at two or more hyperscale cloud providers, such as AWS, Azure, or GCP.
  • 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...
  • Strong understanding of infrastructure, distributed systems, or SRE practices.
  • 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.

Preferred

  • Previous engineering or SRE experience.
  • 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...
  • 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.

Original job description

Content provided by the employer

P-1489

About Databricks

At Databricks, we are passionate about empowering data teams to tackle the world's most complex challenges — from bringing the next mode of transportation to reality to accelerating the development of medical breakthroughs. We achieve this by building and operating the world's best data and AI infrastructure platform, enabling our customers to leverage deep data insights and enhance their business.

The Role

We are seeking an exceptional Senior Staff Technical Program Manager (TPM) for Reliability to lead the strategy, execution, and continuous improvement of our most critical Reliability initiatives across infrastructure and product engineering teams at Databricks. As Databricks scales to support thousands of customers and the world’s most data-intensive workloads, Reliability is foundational to our mission. In this role, you will lead cross-company programs that significantly enhance the reliability, performance, and operational excellence of our multi-cloud infrastructure.

This is a high-visibility, high-impact leadership role partnering closely with our most senior engineering leaders, including Reliability Program executive sponsors, senior TLs, and Engineering Managers to define Reliability strategy, set long-term goals, and execute multi-quarter programs to build the most reliable cloud platform on the planet to help our customers run their mission-critical workloads on. 

To be successful, you must possess a deep understanding of large-scale distributed systems, cloud infrastructure, and engineering principles that drive operational excellence. You will leverage your background to anticipate risks, shape technical direction, and deliver complex programs across product, engineering, SRE, and cloud partner teams.

You will have the opportunity to:

Lead Reliability Strategy + Multi-Quarter Roadmaps

  • Partner with senior engineering leadership to define the long-term Reliability roadmap, influence technical direction, and ensure alignment across teams.
  • Ensure clarity and alignment on priorities across engineering teams, including Platform Engineering, Compute Fleet Management, SRE, Security, and Cloud Partnerships.

Drive Execution of Critical Reliability Programs

  • Own program execution end-to-end: planning, risk management, dependency mapping, trade-off decisions, status reporting, and delivery.
  • Identify gaps in process or architecture and work with TLs to proactively drive organizational or technical improvements.

Partner Deeply with Engineering & Influence Technical Direction

  • Using your background in infrastructure, distributed systems, or SRE to help teams make sound design and prioritization decisions.
  • Facilitate alignment between cross-functional teams to ensure programs are technically grounded and execution-ready.
  • Bring systems thinking to diagnose reliability bottlenecks and drive improvements to scalability, fault tolerance, automation, and operational tooling.

Elevate Reliability Culture Across the Organization

  • Drive adoption of reliability best practices across engineering teams - including error budgets, incident reviews, design-for-resilience patterns, and operational readiness.
  • Define and implement program governance, repeatable processes, metrics, and documentation to scale reliability efforts across teams.
  • Evangelize reliability expectations and engineer-empowering processes that reduce operational load and improve incident preparedness.

What we look for:

Required Experience & Qualifications

  • 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.

Preferred Qualifications

  • 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.



 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

 

Local Pay Range
$189,800$256,160 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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Databricks

About the company

Databricks

Large Enterprise

Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.