Interested in joining a technically driven Commodities trading fund?
You're going to be working on a tight-knit data engineering team, side-by-side with world class traders and data scientists in the front office. It's a position that'll have you assisting on everything data-related, from data architecture design to on-going data management, you'll have your work cut out for you.
They're recognized globally as a top commodities trading firm, largely focused on data science and have been ramping up their presence generative AI space. They bring in 100's of billions of rows of data that the Data Engineers model/architect for the Data Science team to build Machine Learning models using time series data.
To give you a better idea, they recently completed a project that tracked cargo vessel's raw data shipping locations (330 million records) in a specific regions to help Data Science build a Supply & Demand Machine Learning model.
Upon joining, you'd jump right into a data migration project where you'd be loading on-prem Oracle into Snowflake data warehouses. You'll create data ingestion pipelines using lots of Python and SQL, work extensively with ETL frameworks to write pipelines to load millions of records, and build dashboards with business intelligence tools like Power BI and Tableau. Additionally, bonus points if you have any experience with machine learning or artificial intelligence since you'll gain more exposure with those technologies as you progress in the role.
Given the cross-collaborative nature of the position, you'll need to be comfortable working on-site 3x per week in their Stamford HQ office. It'll give you significant exposure to their Risk and commercial investing teams globally.
Looking for a fast-paced, front office, fundamentally data focused role? Apply today.
