Big Data Solutions Engineer

As one of the world’s largest financial services companies, Prudential’s individual and institutional customers rely on us to protect and grow their financial well being.

- Build distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time. - Collaborate with other teams to design and develop and deploy data tools that support both operations and product use cases. - Perform offline analysis of large data sets using components from the Hadoop ecosystem. - Evaluate and advise on technical aspects of open work requests in the product backlog with the project lead. - Own product features from the development phase through to production deployment. - Evaluate big data technologies and prototype solutions to improve our data processing architecture.

- BS in Computer Science or related area - 10-12 years software development experience - Minimum 2 Year Experience on Big Data Platform - Proficiency with Java, Python, Scala, HBase, Hive, MapReduce, ETL, Kafka, Mongo, Postgres, Visualization technologies etc. - Flair for data, schema, data model, how to bring efficiency in big data related life cycle - Understanding of automated QA needs related to Big data - Understanding of various Visualization platform (Tableau, D3JS, others) - Proficiency with agile or lean development practices - Strong object-oriented design and analysis skills - Excellent technical and organizational skills - Excellent written and verbal communication skills Top skill sets / technologies in the ideal candidate: * Programming language -- Java (must), Python, Scala, Ruby * Batch processing -- Hadoop MapReduce, Cascading/Scalding, Apache Spark * Stream processing -- Apache Storm, AKKA, Samza, Spark streaming * NoSQL -- HBase, MongoDB, Cassandra, Riak, * ETL Tools – Data Stage, Informatica, * Code/Build/Deployment -- git, hg, svn, maven, sbt, jenkins, bamboo