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.
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.
- 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.
- 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.
- 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.
- 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.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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, please visit https://www.mybenefitsnow.com/databricks.
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.
Top Skills
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
