At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.
Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.
Our engineering teams build technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.
We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
As a Senior Frontend Engineer, you will work closely with your team and product management to bring that delight through a great user experience. We are seeking engineers with a track record of being customer-obsessed, who can build an elegant user experience for the enterprise customers to process data at a massive scale. You'll set the foundation for how we build robust, scalable, and delightful products.
Below Are Some Example Teams You Can Join:
Clusters UI: Build the compute fabric powering all the workloads executed on the platform and the services necessary for managing Apache Spark workloads. The team also provides Databricks' customers with fast and easy ways to provision Spark clusters, and empower advanced use cases that enable cloud features, services, and data sources.
Delta Pipelines: The mission of this team is to enable customers to successfully deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines. The UI is critical to the success of this product. It sets the tone for the simplicity and intuitiveness of configuring and monitoring these pipelines.
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.
Redash: Provide a great SQL-centric data exploration and visualization experience on Databricks, leveraging Redash, the most popular open-source project in this area. With Redash, we enable Databricks users to explore, query, visualize and share data using SQL, to develop insights and make data-driven decisions without the need to master complex software
Workspace: The Databricks Workspace provides an interactive environment for collaborative data projects at massive scale with an easy path to production. Data engineers, analysts, ML practitioners, and data scientists use the workspace for the full lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. The Workspace is a SaaS service that is used by hundreds of thousands of data scientists daily.
Clusters UI: Build the compute fabric powering all the workloads executed on the platform and the services necessary for managing Apache Spark workloads. The team also provides Databricks' customers with fast and easy ways to provision Spark clusters, and empower advanced use cases that enable cloud features, services, and data sources.
Delta Pipelines: The mission of this team is to enable customers to successfully deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines. The UI is critical to the success of this product. It sets the tone for the simplicity and intuitiveness of configuring and monitoring these pipelines.
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.
Redash: Provide a great SQL-centric data exploration and visualization experience on Databricks, leveraging Redash, the most popular open-source project in this area. With Redash, we enable Databricks users to explore, query, visualize and share data using SQL, to develop insights and make data-driven decisions without the need to master complex software
Workspace: The Databricks Workspace provides an interactive environment for collaborative data projects at massive scale with an easy path to production. Data engineers, analysts, ML practitioners, and data scientists use the workspace for the full lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. The Workspace is a SaaS service that is used by hundreds of thousands of data scientists daily.
Clusters UI: Build the compute fabric powering all the workloads executed on the platform and the services necessary for managing Apache Spark workloads. The team also provides Databricks' customers with fast and easy ways to provision Spark clusters, and empower advanced use cases that enable cloud features, services, and data sources.
Delta Pipelines: The mission of this team is to enable customers to successfully deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines. The UI is critical to the success of this product. It sets the tone for the simplicity and intuitiveness of configuring and monitoring these pipelines.
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.
Redash: Provide a great SQL-centric data exploration and visualization experience on Databricks, leveraging Redash, the most popular open-source project in this area. With Redash, we enable Databricks users to explore, query, visualize and share data using SQL, to develop insights and make data-driven decisions without the need to master complex software
Workspace: The Databricks Workspace provides an interactive environment for collaborative data projects at massive scale with an easy path to production. Data engineers, analysts, ML practitioners, and data scientists use the workspace for the full lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. The Workspace is a SaaS service that is used by hundreds of thousands of data scientists daily.
Clusters UI: Build the compute fabric powering all the workloads executed on the platform and the services necessary for managing Apache Spark workloads. The team also provides Databricks' customers with fast and easy ways to provision Spark clusters, and empower advanced use cases that enable cloud features, services, and data sources.
Delta Pipelines: The mission of this team is to enable customers to successfully deploy, test & upgrade pipelines and eliminate operational burdens for managing and building high quality data pipelines. The UI is critical to the success of this product. It sets the tone for the simplicity and intuitiveness of configuring and monitoring these pipelines.
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.
Redash: Provide a great SQL-centric data exploration and visualization experience on Databricks, leveraging Redash, the most popular open-source project in this area. With Redash, we enable Databricks users to explore, query, visualize and share data using SQL, to develop insights and make data-driven decisions without the need to master complex software
Workspace: The Databricks Workspace provides an interactive environment for collaborative data projects at massive scale with an easy path to production. Data engineers, analysts, ML practitioners, and data scientists use the workspace for the full lifecycle from loading data, visualizing results, creating statistical models, and deploying as production artifacts. The Workspace is a SaaS service that is used by hundreds of thousands of data scientists daily.
What we look for:
Benefits
About Databricks
Databricks is the data and AI company. Thousands of organizations worldwide — including Comcast, Condé Nast, Nationwide and H&M — rely on Databricks' open and unified platform for data engineering, machine learning and analytics. Databricks is venture-backed and headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world's toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.