Databricks

Staff Software Engineer - Backend

Databricks$192K — $260K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • BS/MS/PhD in Computer Science or related field
  • 10+ years of production-level experience in Java, Scala, C++, or similar
  • Proficient in architecting, developing, deploying, and operating large-scale distributed systems
  • Experience with SaaS platforms or Service-Oriented Architectures
  • Strong knowledge of SQL
  • Familiarity with cloud technologies such as AWS, Azure, GCP, Docker, Kubernetes
  • Understanding of software security and sensitive data handling

Responsibilities

  • Design and implement micro-services for the Databricks platform
  • Write software primarily in Scala/Java
  • Build and maintain data pipelines using Apache Spark and Kafka
  • Integrate with third-party applications and interact with cloud APIs
  • Collaborate with team and product management on project prioritization
  • Develop infrastructure for high-performance data storage and access
  • Create reliable services and infrastructure for managing data teams

Benefits

  • Comprehensive health coverage
  • Flexible working hours and remote work options
  • Equity options
  • Annual performance bonuses
  • Professional development opportunities
Full Job Description
P-150

As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform).

Below are some example teams you can join:

Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our technology empowers the flagship collaborative workspace, notebooks, IDE integrations, and project management products. We also enable machine learning at scale with tools for environment management, distributed training, and managing the Machine Learning lifecycle through MLflow.

Compute Fabric: Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic way. The software manages millions of virtual machines.

Data Plane Storage: Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store.

Enterprise Platform: Offer a simple and powerful experience for onboarding and managing all of their data teams across 10ks of users on the Databricks platform. We do this by building reliable, scalable services and infrastructure with intuitive UIs and by delivering high-impact, cross-cutting projects that drive the "land and expand" strategy for enterprise customers.

Observability: Provide a world class platform for Databricks engineers to comprehensively observe and introspect their applications and services. We build scalable data-intensive infrastructure that processes huge amounts of logs and telemetry. By doing so, we enable teams to become more data-driven and build robust services.

Service Platform: Build high-quality services and manage the services in all environments in a unified way. We provide engineers libraries, tools, services and guidance to develop reliable, scalable, and secure services. We build a unified platform for engineers to deploy and update their services across different clouds and environments.

Core Infra: Build the core infrastructure that powers Databricks, making it available across all geographic regions and Cloud providers. We build highly available distributed systems, heavily utilizing cloud native projects, contributing back whenever possible. We run thousands of Kubernetes clusters across all regions and orchestrate millions of VMs on a daily basis.

Competencies
  • BS/MS/PhD in Computer Science, or a related field
  • 10+ years of production level experience in one of: Java, Scala, C++, or similar language.
  • Comfortable working towards a multi-year vision with incremental deliverables.
  • Experience in architecting, developing, deploying, and operating large scale distributed systems.
  • Experience working on a SaaS platform or with Service-Oriented Architectures.
  • Good knowledge of SQL.
  • Experience with software security and systems that handle sensitive data.
  • Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes.


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

$192,000-$260,000 USD

BenefitsAt 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.

About Databricks

Databricks is a unified analytics platform that provides data engineering, collaborative data science, and machine learning capabilities. The company was founded in 2013 by the original creators of Apache Spark, a popular open-source big data processing engine. Databricks provides a cloud-based platform that allows data teams to collaborate and build data pipelines, run machine learning models, and perform advanced analytics. The company has raised over $1 billion in funding and is valued at $38 billion as of November 2021.
Learn more about Databricks
Size
2,000 employees
Industry
Founded
2013

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