Data Engineer – Commodities

Role Overview

The Commodities Technology team builds and operates a data platform that aggregates and curates critical commodities data. The team develops flexible, scalable technology and proprietary systems that support advanced analytical and trading capabilities.

What You Will Do

Design, implement, and maintain end-to-end ETL workflows in Python and SQL to ingest and transform commodities data. Build and maintain standardized data models, schemas, and metadata. Schedule, monitor, and manage data pipelines using Airflow or similar workflow orchestration tools.

Why It Might Be a Fit

5+ years of experience in data engineering, analytics engineering, or a similar role building and maintaining ETL pipelines. Strong Python and SQL skills, including experience working with large datasets and complex data transformations.

Requirements

• 5+ years of experience in data engineering, analytics engineering, or a similar role building and maintaining ETL pipelines
• Strong Python and SQL skills, including experience working with large datasets and complex data transformations
• Hands-on experience with Airflow or comparable workflow orchestration tools
• Experience with Git, CI/CD pipelines such as GitHub Actions, and automated testing frameworks such as PyTest
• Strong attention to detail, data quality, and documentation, with the ability to identify edge cases and protect data integrity
• Ability to work independently, communicate effectively with technical and non-technical stakeholders, and manage multiple concurrent initiatives