- Entry level
- No Education
- Salary to negotiate
- Palo Alto
Since its origin, Cloudera has enabled customers to effectively manage and gain insight into their data leveraging both on-premises and cloud infrastructure. We are now working on providing a unified data platform that enables customers to effortlessly access, manage and leverage data -- regardless of where it resides. This platform will enable enterprises to run data applications such as Machine Learning and Data Warehousing., while providing security and governance to the underlying data. The Cloud team is focused on at least two major areas - Control Plane and Workload Enablement.
The Control Plane is the point of access for Cloudera’s cloud service for customers. It enables a coherent experience for operators of enterprise data clouds to manage and provision workloads for their users. Key considerations in building the control plane include robustness, scalability, portability and consistent APIs whether the control plane is operated by Cloudera or by customers, in public clouds or private datacenters. The Control Plane, built on top of Kubernetes, provides user management, telemetry on clusters running the workloads, defines ways to deploy and launch services and workloads, billing, metering, etc.
The Workload Enablement area involves things like Cloud Storage Connectors. This is being able to use cloud storage (s3, etc.) effectively (being secure, optimal and consistent) from the workload clusters running in the cloud. The other areas are to do with things like being able to react to cloud VM failures, things like autoscaling of workloads, security infrastructure for workloads, etc.
Skillsets: Operating Systems and Filesystem internals, Java, Go, Kubernetes, Microservices architecture and implementation, Performance benchmarking, experience with AWS, Azure or GCP.
Technologies Used: Kubernetes, Hadoop, REST, AWS / Azure / GCP Cloud technologies
About the company
Cloudera, Inc. is a US-based software company that provides a software platform for data engineering, data warehousing, machine learning and analytics that runs in the cloud or on premises.