Data Engineer - Python Developer - Remote

Overview

The Data Engineer will work within the S&P Global Commodity Insights team, focusing on developing and automating processes and models that enhance commodity analytics.

In Short

• Develop and automate commodity models using statistical techniques.
• Collaborate with data analysts and product management teams.
• Manage end-to-end analytical modeling projects.
• Utilize Python, SQL, and Excel for data manipulation.
• Implement data automation and machine learning solutions.
• Lead projects and coordinate junior analysts.
• Ensure high-quality data governance and monitoring.
• Work in an Agile development environment.
• Communicate insights effectively to stakeholders.
• Contribute to the enhancement of analytics content.

Requirements

• Bachelor’s degree in relevant field (Engineering, Mathematics, etc.).
• Fluent in English, both conversational and written.
• Minimum of 3 years in a similar role.
• Experience with analytical modeling projects.
• Strong communication and relationship-building skills.
• Proficiency in SQL, Excel, and Python.
• Experience with data automation and machine learning.
• Ability to lead projects and teams.
• Preferred: Master’s degree in relevant field.
• Preferred: Experience in the commodity space.

Benefits

• Health care coverage for well-being.
• Generous time off policies.
• Access to continuous learning resources.
• Competitive pay and retirement planning.
• Family-friendly perks.
• Retail discounts and referral incentives.