Quantitative Developer
Responsibilities:
- Design and deploy robust ETL pipelines for fundamental research and reference data
- Ensure data lineage, quality, and timelines across critical research/reporting workflows
- Maintain SQL databases and ingested datasets
- Build and maintain scalable data infrastructure to ensure automate research tasks/reports, including but not limited to inhouse python packages, web applications, MSSQL functions/stored procedures
Requirements:
- Strong Python development skills, especially in data engineering or quant development context including:
- Market data APIs/Web scraping
- Timeseries modelling and visualization (pandas, statmodels, plotly, folium, etc.)
- Building reunsable python models to streamline regular workflow (STMP, pyodbc, etc.)
- Prior experience working on a commodities trading desk or working with US Natural Gas trading required
- Strong SQL experience and knowledge in data modelling, complex query and performance tuning, stored procedures and functions, and index management
- Excellent debugging and problem solving skills
- Experience with ETL orchestrators like Visual Cron, Jenkins and Airflow
- Familiar with Git, Azure DevOps, Snowflake
- Ability to collaborate effectively across multiple US offices with diverse stakeholders
- Experience handling multi-dimensional datasets (weather, sattelite signals, commodity flows)
- Knowledge of machine learning frameworks (scikit-learn, xgboost, etc.)
- Experience in optimizing cloud costs and large-scale data storage, ensuring operations remain efficient and cost effective