Senior Staff Software Engineer - Serverless Efficiency Mountain View, California

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Team Serverless Compute Platform Team is responsible for building the compute infrastructure for all of Databricks Serverless product lines. As the TL for Serverless Compute Efficiency at Databricks, you will have the opportunity to lead the charter on reducing our costs and improving product margins. Your job is to identify, define, design and deliver these projects by leading other engineers, and by working closely with product teams and partner clouds. The impact you will have: Develop a framework for understanding and tracking costs closely, working closely with Data Science teams. Work closely with Product teams to understand the performance-cost tradeoffs and make those choices available in the Platform APIs. Work closely with Cloud partners to align on the right Compute platforms to meet the product needs efficiently. Develop a roadmap of Engineering projects that span 12-24 months, with progressive improvement in product margins. Lead the team effectively to drive disciplined execution against the roadmap. What we look for: Candidates should have multiple years of experience in building and running large scale and mission critical infrastructure systems. Candidates must have experience in leading complex, cross-team, cross-layer, multi-quarter projects. Experience in developing and operating large scale distributed systems. Experience in leading large / complex, multi-quarter technical projects. Experience with leading Compute Efficiency projects. Strong cross-team collaboration - leading without authority. Strong at execution - project progress and dependency tracking. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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. Local Pay Range $232,000 — $313,000 USD 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. 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

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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