Strong experience in Python and either Java or Scala
Experience with large applications and systems development
Strong experience using JDBC for database access
Strong database and blob storage experience
Experience integrating applications with cloud data storage systems like S3, GCS, Azure Blob Storage, etc.
Experience with authentication methods like Kerberos, SSO, Active Directory or similar
Familiarity with HTTP and experience using tools such as curl or Postman to test HTTP APIs
Ability and willingness to quickly learn about new technologies
Experience with Kubernetes ecosystem or Hadoop ecosystem
Experience developing applications using Docker
Experience with Gradle or other build systems
Experience with functional programming
As an Ingest Backend Engineer, you will develop ingest systems to integrate DataRobot with databases, cloud storage systems, SaaS products, and other sources of data, and you will help enhance and maintain these systems as they evolve to meet future connectivity and performance needs. You will contribute to the design of new frameworks to support reading, writing, authentication, failure handling, and more with high performance and reliability. These ingest systems are a key component of the overall architecture of DataRobot.
Ideally, a candidate can bring new ideas from concept to implementation, write quality, testable code, and participate in design/development discussions. They also have a can-do attitude and highly value the customer experience above all else, and embrace maintaining and firefighting systems when necessary. The ability and willingness to quickly learn new technologies are essential for this role.
The Global Data Domain at DataRobot helps make AI incredibly easy to build by surfacing and connecting users to all enterprise data, and enabling data prep at modeling and prediction time. In this role, you’ll help enable our users to easily interact with the data required to train models and generate predictions. Additionally, you’ll help design solutions that foster collaboration amongst distributed teams of engineers, data scientists, and beyond.