Senior Software Engineer - Backend

Databricks
San Francisco, CaliforniaPosted 7 April 2026

Job Description

P-78 At Databricks, we are passionate about enabling data teams to 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. As a software engineer with a backend focus, you will work with your team to build infrastructure and products for the Databricks platform at scale. The impact you'll have: Our backend teams span many domains, from our core compute fabric resource management infrastructure, to service platforms, to machine learning infrastructure. For instance, you might work on challenges such as: Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way Develop reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers Build tools to allow Databricks engineers to operate their services across different clouds and environments Build services, products and infrastructure at the intersection of machine learning and distributed systems. What we look for: BS (or higher) in Computer Science, or a related field 5+ years of production level experience in one of: Java, Scala, C++, or similar language. Experience developing large-scale distributed systems. Experience working on a SaaS platform or with Service-Oriented Architectures. Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes. Experience with security and systems that handle sensitive data. Good knowledge of SQL. Benefits Comprehensive health coverage including medical, dental, and vision 401(k) Plan Equity awards Flexible time off Paid parental leave Family Planning Gym reimbursement Annual personal development fund Work headphones reimbursement Employee Assistance Program (EAP) Business travel accident insurance 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 $166,000 $225,000 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. 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 Commitme ... (truncated, view full listing at source)
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