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Databricks

Sr Software Engineer, Infrastructure

San Francisco, California, United States

Location
San Francisco, California, United States
Work
Not stated
Employment
Not stated
Level
Senior
Function
Engineering
Pay
$159.9K – $219.9K a year
Posted
6 months ago

About the role

GAQ127R41

Location: San Francisco, CA (Hybrid)

About the Role

At Databricks Information Technology, we are a product-led organization transforming the way we work, from how easy it is to use our IT services to the applications we develop that help us scale seamlessly in the face of incredible growth.

As a Senior Software Engineer (Infrastructure), you will be a core technical contributor on the IT Infrastructure team, owning and driving the evolution of our core infrastructure and observability platforms. This role requires a strong software engineering mindset, deep technical breadth across SRE and infrastructure worlds, and the ability to deliver high-quality, scalable solutions for currently "immature" system problems. You will be responsible for building resilient, scalable, and automated infrastructure that empowers our development teams. As a senior member of the team, you will bridge the gap between software engineering and systems architecture, ensuring our AWS environment is cost-optimized, secure, and highly available.

The Impact You Will Have

  • Architect and Automate: Design and deploy production-grade infrastructure on AWS using Terraform or Pulumi.
  • Orchestration: Manage and scale containerized workloads using AKS (Azure Kubernetes Service) or EKS, focusing on cluster security and resource efficiency.
  • CI/CD Excellence: Architect robust deployment pipelines using GitHub Actions, managing both GitHub-hosted and self-hosted runners for specialized build requirements.
  • Drive "Observable by Default" Frameworks: Create underlying infrastructure to ensure new internal applications are secure and have logging and metrics enabled by default
  • Tooling, Scripting & AI : Build internal CLI tools,AI plugins and automation scripts to streamline developer workflows and enhance operational efficiency
  • Partner Cross-Functionally: Collaborate with stakeholders across Security, Engineering, Infrastructure, and Support to deliver impactful projects with real business outcomes.
  • Mentor and Document: Participate in Code reviews, Document solutions and failure triage playbooks, and mentor junior engineers on the platforms you own.

What We Look For

  • Software Engineering Expertise: 5+ years of production-level experience with a strong proficiency in Python (non-negotiable).
  • IaC: Expert-level proficiency in Terraform (modules, state management) or Pulumi(Preferred).
  • Cloud & Infrastructure Breadth: Hands-on experience with AWS (or Azure/GCP), Kubernetes, Docker and containerization concepts.
  • Automation & Integration Mindset: Experience building and troubleshooting integrations between infrastructure, data pipelines, and observability platforms.
  • CI/CD: Advanced knowledge of Github Actions, Github Runners.
  • Strong Observability Mindset: Understanding of observability pillars (logging, metrics, tracing) and hands-on experience with tools like Datadog, Prometheus, or ELK.
  • Distributed Systems: Proficiency in running systems through concepts like Kafka or messaging queues.
  • Independent Execution: Ability to operate with minimal guidance, take ownership of ambiguous projects, and follow a vision set by tech leads to execute independently.

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.

Zone 1 Pay Range

$159,900—$219,900 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.

Source

Posted by Databricks on their own hiring page, databricks.com. OptiTalent shows it as published, read 07 Nov 2026 01:45 UTC; the original is the reference.

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