As a Scaleout Engineer, you will build out Data Management and ETL system inside DataRobot utilizing distributed frameworks such as Spark, Hadoop and Kubernetes. You will build scalable solutions to process high data volumes, with the main focus on crafting robust components for data intake, cleanup and full variety of data transformation. You will also be responsible for designing and implementing features from start to finish, including clean and easy to use APIs, automated tests, and deployment infrastructure.

The ideal candidate can bring new ideas from concept to implementation, write quality, testable code, and participate in design/development discussions.

Main Requirements

• 5+ years of experience in Python or a JVM based language, such as Java or Scala
• 3+ years of experience in architecting and developing distributed systems
• Experience with data processing using at least one of the following tools:
• Spark
• Dask
• Pandas
• Experience with Hadoop ecosystem
• In the interview process, you will be evaluated on your performance in a number of coding and design scenarios - be prepared to think!

Desired Skills

• Ability to communicate about technical topics
• Willingness to learn about new technologies
• Experience in some or all of the following:
• System/performance evaluation such as profiling process memory/cpu/io/network usage and language-specific debugging tools
• Document-oriented databases, ideally MongoDB
• Distribute search engines such as ElasticSearch or Solr
• Messaging services such as RabbitMQ
• Hadoop services such as Yarn, Spark and HDFS
• Docker
• Kubernetes