WorldQuant is a quantitative asset management firm founded in 2007 and currently has over 500 employees globally. We
develop and deploy systematic financial strategies across a variety of asset classes in global markets, utilizing a proprietary
research platform and risk management process.
As a Data Engineer at WorldQuant you will work on the design, deployment and support of very large scale data systems that
are the backbone of the company. The primary focus will be on implementing, maintaining, and monitoring them. You will
also be responsible for integrating them with various other systems across the company.
Your responsibilities will include:
- Defining data models and schemas based on various business requirements
- Implementing high volume data pipelines
- Defining and enforcing data retention policies
- Monitoring performance and providing recommendations on necessary infrastructure changes
- Developing interfaces and micro services in Python, C++ and/or Java/Scala that will connect users to data provided by our services
Our ideal candidate will have a strong background in software development, great interpersonal skills, and familiarity with
systems administration and/or integration. In addition, the candidate will have:
- A bachelor’s degree in a technical or quantitative field
- At least 5 years of experience as a data engineer or software developer
- Outstanding software development skills
- A passion for Data Engineering and Data Science
- Experience with NoSQL databases, such as Cassandra, HBase, or MongoDB (Cassandra preferred)
- Good knowledge of Big Data querying tools, such as Pig or Hive
- Experience with building stream-processing systems, using solutions such as Spark-Streaming or Kafka-Streaming a very
- Experience with integration of data from multiple data sources a big plus
Candidates need not have prior experience in financial services.