A top investment manager with offices around the world is looking to bolster one of their marquee data technology teams in their New York City office. Data infrasturcture, technology, and the surrounding ecosystem has been a major part of the firms revenue generation for many years - and more recently an epicenter for the firm's use cases for AI/ML.
As a Data Engineer, you would partner with users across the business on solving some of their hardest problems with data solutions. Specifically, you’ll collaborate closely with quantitative researchers and developers to design, develop, and optimize the systems that drive cutting-edge investment research and trading.
Responsibilities
- Devlop and deploy high-performance, fault-tolerant data systems to support large-scale research and trading.
- Develop and manage efficient ETL/ELT pipelines to streamline data ingestion, transformation, and enrichment.
- Create intuitive dashboards and analytics tools that illuminate data health, usage, and impact.
- Build data observability and reporting solutions to inform strategy and operational decisions.
- Develop reusable software components and curated datasets to accelerate research and LLM applications.
Requirements
- Skills in Python, SQL
- Experience in Airflow or Spark
- 3+ years of progressional experience as a Data Engineer
- Strong sense of ownership and collaboration
- Experience with Snowflake, Databricks, or Redshift
- An understanding of AI/ML principles
