A major Investment bank in NYC is looking for the following

We are building a strategic reference data platform for client, account and instrument data. Platforms initial rollouts have been extremely successful and we are looking to expand and extend. We need top-tier engineers who have a strong and successful track record of solving hard problems and out of the box thinking. We work in a dynamic environment and expect new joiners to be flexible, self-sufficient and learn our business, our data and our technology stack with minimal supervision. They will lead the push for horizontally scalable, high performance applications, while facing off to senior business and tech partners across the organization. Prime role for strong, independent individual contributor, with huge growth potential.

- 5+ years of Scala, Java, Python (or similar) programming
- Familiar with functional programming style (Scala, Java 8 w/ lambda expressions, etc.)
- Strong problem-solving and communication skills and enjoys a collaborative environment
- Flexible, self-starter, fast-learner - willing and able to quickly learn new technologies and skills
- Experience with functional programming is a big plus
- Experience with graph technologies is a plus. Familiarity with Semantic Web (RDF) and Sparql is a plus
- Experience with distributed computing is a plus. Familiarity with Zookeeper/Storm/Spark/HDFS is a plus.
- Experience with search technologies is a plus. Familiarity with Lucene/Solr/ElasticSearch is a plus
- Experience with enhancing and maintaining mission-critical software in a fast-paced environment is a plus

****Some more dos and donts for recruiting team************

Desired characteristics, in order of priority:

- Ability to work independently - take nothing for granted, ask questions, learn the business, desire to understand not only what to do, but also why.
- Scala knowledge or experience (or demonstrated desire to learn on their own)
- Deep, hands-on knowledge and experience in building applications, end to end, in Java, Python or C++.
- RDF / Symantic Web / noSQL DB knowledge or experience (ex. MongoDB)
- Exposure to distributed frameworks (hbase, hadoop, spark)
- Knowledge/experience in the credit derivatives space
- Knowledge/experience in reference data (client or product)
- Background or demonstrated interest in machine learning algorithms