# Senior Software Engineer - Infrastructure and Tools at Databricks > United States · Senior · DevOps / SRE / Infra · open. Source: https://alderhq.app/jobs/greenhouse%3Adatabricks%3A6318503002 (read 2026-11-04). ## Facts (observed) - Company: [Databricks](https://alderhq.app/companies/databricks) - Location text: San Francisco, California; San Francisco, California - Where it can be done from (inferred): United States (evidence: "Location: San Francisco, California; San Francisco, California") - Posted: 2022-08-10 (1548 days ago) - First seen by alder: 2026-11-03 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://databricks.com/company/careers/open-positions/job?gh_jid=6318503002 - Skills listed (inferred): Python, Go, Java, Scala, C++, AWS, GCP, Azure, Kubernetes, Docker, Terraform, Distributed systems ## Pay and sponsorship - Posted pay: $166k–$225k per year (from the listing's pay field) - Market band for similar posted roles (SF Bay Area, n 97): p25 $190k, median $213k, p75 $229k - H-1B filings at this company for similar roles, FY26: 356, median offered wage $157k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) - Recognised sponsor (NL): registered as "Databricks" (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants)) - Licensed UK sponsor: registered as "Databricks UK Limited" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) P-78 While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered. 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 Senior Software Engineer on the Infrastructure teams, you will build scalable systems to power the Databricks platform, making it the de-facto platform for running Big Data and AI workloads. You will build and extend the Databricks infrastructure platform, which includes multi-cloud systems and services for managing thousands of Kubernetes clusters at scale, storing petabytes of data, highly scalable and distributed API gateways, rate limiting framework, network security and encryption, developer tools and infrastructure (we use Bazel), testing frameworks, and scalable CI/CD framework among many others. ### The impact you will have - Build and extend components of the core Databricks infrastructure - Architect multi-cloud systems and abstractions to allow the Databricks product to run on top of existing Cloud providers - Improve software development workflows for engineering and operational efficiency. - Use our own data and AI platform (yes!) to analyze build and test logs and metrics to identify areas for improvement. - Develop automated build, test, and release infrastructures. - Set and uphold the standard for engineering processes to support high-quality engineering, including style and code checking, test harnesses, and release packaging. ### What we look for - BS (or higher) in Computer Science, or a related field - 5+ years of experience writing production code in one of: Java, Scala, Go, C++ or Python - Passion for building highly scalable and reliable infrastructure - Experience architecting, developing and deploying large-scale distributed systems at scale - Experience with cloud APIs (e.g., a public cloud such as AWS, Azure, GCP or an advanced private cloud such as Google, Facebook) - Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes, or Terraform. ### 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 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Adatabricks%3A6318503002 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.