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