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A global investment management firm in Singapore is seeking an experienced Data Engineer to join its data engineering team. The role involves building enterprise data assets with financial datasets and collaborating across teams. Candidates should have a STEM degree and over 3 years of programming experience in Python and/or Java, along with knowledge of data modeling and AWS technologies.
ExodusPoint Capital, founded in 2017 by Michael Gelband, began managing investor capital in 2018. The firm employs a global multi-strategy investment approach, seeking to deliver compelling asymmetric returns by combining complementary liquid strategies managed by experienced investment professionals within a robust risk framework. ExodusPoint brings together an accomplished team with hands-on experience running multi-manager businesses to create an institutional investment management firm.
ExodusPoint is seeking an experienced Data Engineer with financial data knowledge to join an established data engineering team to help build a next generation data offering for ExodusPoint’s diverse investment teams, varying across asset classes and strategies. The ideal candidate is a domain expert on financial datasets who has technical skills to work with business and create enterprise data assets utilizing advanced data processing techniques and tools.
The Enterprise Data group is focused on building a robust data platform which services a diverse set of investment teams and internal clients. The group consists of data sourcing experts, data product specialists, data scientists and data engineers, who are responsible for the discovery, management, and curation of thousands of alpha sources for the firm and our investment professionals.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.