Join Databricks as a Site Reliability Engineer to build resilient, automated infrastructure and enhance operational efficiency.
Posted by employer 4 months ago
First seen on Joblaze 4 months ago
Last verified on the company career page 6 hours ago
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In the role of Site Reliability Engineer at Databricks, the individual will focus on enhancing the IT infrastructure by designing and automating resilient cloud systems. Key skills include expertise in Python, Infrastructure as Code with Terraform or Pulumi, and experience with cloud platforms like AWS or Azure. This position is ideal for seasoned professionals with a strong software engineering background who can independently manage complex projects. Databricks emphasizes a collaborative environment, partnering with various teams to drive operational excellence.
Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this Sr. IT Site Reliability Software Engineer role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, Azure, Datadog, Docker, ELK, GCP.
- What seniority level is this role?
- Databricks targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Sr. IT Site Reliability Software Engineer role at Databricks.
From the original posting
GAQ127R40
Team: IT Infrastructure and Operations
About the Role
At Databricks Information Technology, we are a product-led organization transforming how we work—from the ease of using our IT services to the applications we develop to scale seamlessly during rapid growth.
As a Site Reliability Engineer (SRE), you will bridge the gap between software engineering and systems architecture. You will be a core contributor to the IT Infrastructure team, owning the evolution of core infrastructure and observability platforms. This role requires a strong software engineering mindset and deep technical breadth to deliver high-quality, scalable solutions for "immature" system problems. Your focus will be on building resilient, automated infrastructure that empowers development teams and ensures our cloud environment is cost-optimized, secure, and highly available.
The Impact You Will Have
- Architect and Automate: Design and deploy production-grade infrastructure on cloud platforms (AWS/Azure) using Infrastructure as Code (IaC) tools like Terraform or Pulumi.
- Reliability and Performance Engineering:Optimize system performance, architecture, and scaling to ensure maximum uptime and minimal latency for critical IT services.
- CI/CD Excellence: Architect robust deployment pipelines (e.g., GitHub Actions), managing both hosted and self-hosted runners for specialized build requirements.
- Observable by Default: Create underlying infrastructure to ensure new internal applications are secure and have logging, metrics and alerts enabled by default.
- Agentic ToolingI: Build internal AI plugins, and automation scripts to streamline developer workflows and enhance operational efficiency.
- Incident Response: Focus on subsequent data usage, incident management workflows, and creating necessary dashboards to maintain service health. Participate in a shared on-call rotation, leading rapid incident response and technical troubleshooting for production outages.Facilitate blameless post-mortems to identify root causes and implement permanent preventive engineering solutions.
- Partner Cross-Functionally: Collaborate with Security, Engineering, and Support teams to deliver real business outcomes.
What We Look For
- Software Engineering Expertise: 5+ years of production-level experience with strong proficiency in Python (non-negotiable).
- Infrastructure as Code (IaC): Expert-level proficiency in Terraform (modules, state management) or Pulumi.
- Cloud & Containers: Hands-on experience with AWS, Azure, or GCP, along with Kubernetes, Docker, and containerization concepts.
- Observability Mindset: Deep understanding of observability pillars (logging, metrics, tracing) and experience with tools such as Datadog, Prometheus, or ELK.
- Distributed Systems: Proficiency in running systems using concepts like Kafka or messaging queues.
- CI/CD Proficiency: Advanced knowledge of GitHub Actions and GitHub Runners.
- Independent Execution: Ability to take ownership of ambiguous projects, follow a vision set by tech leads, and execute independently with minimal guidance.
Standard company text repeated across Databricks's postings is omitted here.