Senior Software Engineer - Application Traffic team

Databricks

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Mountain View, California First seen 3 weeks ago Last seen 1 hour, 20 minutes ago Greenhouse

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Job Description

AI Summary

• Design and build service-to-service communication systems powering Databricks' infrastructure across thousands of multi-cloud clusters, including ingress control planes, service discovery, and load balancing. • Requires BS in Computer Science or related field with 5+ years designing large-scale distributed systems and strong proficiency in Java, Scala, Go, or C++. • Must have experience with service-oriented architectures, cloud platforms (AWS, Azure, GCP), and container orchestration technologies like Kubernetes and Docker. • Build overload protection systems including intelligent rate limiting and admission control to ensure reliability of mission-critical workloads at scale. • Preferred experience with service discovery, DNS, load balancing, Envoy, or related networking systems; competitive pay with full compensation package including equity and benefits.

P-78

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.

As a Senior Software Engineer on the Application Traffic team, you will design and build the systems that power Databricks’ service-to-service communication across thousands of clusters in a multi-cloud environment. You will also help create abstractions that hide networking complexity from product teams, making connectivity, discovery, and reliability seamless by default.

The impact you’ll have:

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.

What we look for:

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

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 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.

Skills

go kubernetes aws docker java

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Job Information

Company:
Databricks
Location:
Mountain View, California
Job Type:
Internship
Experience Level:
Senior
Source:
Greenhouse
Status:
Active

Activity Score

66 /100

Likely Active (66)

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