The role involves translating application storyboards and use cases into functional applications. The individual will design, build, and maintain efficient, reusable, and reliable code. Responsibilities include identifying bottlenecks and bugs while devising solutions to ensure optimal performance and responsiveness. The position requires developing high-performance and low-latency components for Spark clusters. Furthermore, the role entails interpreting functional requirements into design approaches suitable for a Big Data platform and collaborating with global teams. The individual will also perform software prototype testing and process data using specific platforms to derive insights.

Candidates must possess seven to ten years of experience with Python or Spark. The role requires a minimum of two years of experience in Big Data technologies including HDFS, Map Reduce, YARN, Apache Spark, and Hive. Proficiency in systems analysis, design, architecture, and unit testing is necessary. Additionally, the individual must demonstrate experience with UNIX, LINUX, shell scripting, and SQL.