Senior Software Engineer - Application Traffic team

Databricks
Mountain View, CA, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$166,000.0 - $225,000.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Amazon Web Services Microsoft Azure C++ (Programming Language) Cloud Computing Distributed Systems Domain Name System (DNS) Network Control Service-Oriented Architecture Service Discovery Software Engineering
+7 more
Google Cloud Load Balancing Kubernetes Information Technology Api Gateway Docker Databricks

Job description

You’ll work across three key areas that define Databricks’ networking stack:

  • Ingress Control Plane: Build the control plane for Databricks’ global ingress layer. Enable programming of API gateways with static and dynamic endpoints, simplify service onboarding, and make it easy to expose APIs securely across clouds.
  • Service-to-Service Communication: Design scalable mechanisms for service discovery and load balancing across thousands of clusters. Provide networking abstractions so product teams don’t need to worry about underlying connectivity details.
  • Overload Protection: Build intelligent rate limiting and admission control systems to protect critical services under high load. Ensure reliability and predictable performance for both customer-facing and internal workloads.

Requirements

Do you have experience in Software engineering?, Do you have a Bachelor’s degree?, * BS (or higher) in Computer Science or related field

  • 5+ years of experience designing and building large-scale distributed systems
  • Strong proficiency in one or more languages such as Java, Scala, Go, or C++
  • Experience with service-oriented architectures and large scale distributed systems
  • Familiarity with cloud platforms (AWS, Azure, GCP) and container/orchestration technologies (Kubernetes, Docker)
  • Track record of shipping infrastructure that supports mission-critical workloads at scale

Preferred: background in service discovery, DNS, load balancing, Envoy, or related networking systems

Pay Range Transparency

Benefits & conditions

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.

Local Pay Range $166,000-$225,000 USD, At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

About the company

At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems, from advancing AI research to powering next-generation applications. We do this by building and operating the world’s best data and AI infrastructure platform. Founded by engineers and driven by customer obsession, we embrace the hardest technical challenges, whether it’s scaling distributed systems across multiple clouds or delivering reliable, low-latency communication between thousands of services. And we’re only getting started., 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.

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