Job Description

Location: Chicago, IL (On-site)

Employment Type: Internship

This Financial Data Engineering Intern role at Solar Digital Agro LLC is an on-site position based in Chicago, IL. The intern will support the development and maintenance of financial data infrastructure for trading operations, quantitative research, and risk management.

Day-to-day responsibilities include collecting, processing, and validating market data, trading orders, executions, positions, P&L, and risk metrics . The intern will assist in building automated data pipelines, integrating financial data from broker APIs and external providers, maintaining databases, and developing internal reporting tools.

The intern will collaborate with traders, quantitative researchers, and software engineers to improve data accuracy, reliability, and accessibility. This internship provides hands-on experience in financial data engineering, trading infrastructure, and real-time data processing within a professional trading environment.

• Strong programming skills in Python and SQL , with experience in data processing, automation, and database operations.
• Solid understanding of Data Engineering concepts, including ETL/ELT pipelines, data modeling, data validation, and database management.
• Familiarity with Relational Databases , such as PostgreSQL, MySQL, or similar database systems.
• Experience working with APIs, structured datasets, and data manipulation libraries , including Pandas, NumPy, or comparable tools.
• Interest in Financial Markets and Trading Systems , including equities, ETFs, futures, options, and financial market data.
• Strong Analytical and Problem-Solving Skills , with attention to data accuracy, consistency, and operational reliability.
• Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, Engineering, Financial Engineering , or a related technical discipline.
• Ability to work on-site in Chicago, IL , collaborate effectively with technical and trading teams, and communicate findings clearly.
• Experience with Git, Linux, Docker, cloud platforms, broker APIs, or real-time data processing systems is a plus.
• Familiarity with time-series databases, financial data reconciliation, automated monitoring, or trading infrastructure is preferred but not required.

• Hands-on Financial Data Engineering Experience: Work with real-world market data, trading records, and financial datasets to support research and trading operations.
• Exposure to Professional Trading Infrastructure: Gain practical experience with broker APIs, financial databases, automated data pipelines, and risk-monitoring systems.
• Direct Collaboration: Work closely with traders, quantitative researchers, and software engineers on data-driven projects.
• Technical and Professional Development: Strengthen skills in Python, SQL, database management, API integration, and production-oriented data workflows.
• Meaningful Project Contributions: Opportunities to help build and improve financial data systems used in real trading and research workflows.
• Career Growth Opportunities: Develop practical experience in financial technology, quantitative trading infrastructure, and data engineering.

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