Data Engineering Internship (Summer 2027)

Responsibilities

• Develop and maintain robust data ingestion pipelines from various internal and external sources, including APIs, FTP endpoints, and cloud data providers.
• Develop data ingestion and transformation pipelines using Python and SQL, publishing Snowflake for downstream use in analytics and forecasting tools.
• Work on data architecture and data management projects for both new and existing data sources.
• Design and implement ETL processes to clean, normalize, and store structured and semi-structured data in Snowflake, our core relational data warehouse.
• Analyze data pipeline performance and implement optimizations to improve efficiency and reliability.
• Conduct data quality checks and build validation logic to identify anomalies and ensure data integrity for use by commercial trading and analytics teams.
• Automate data workflows using Python, SQL, and orchestration tools (e.g., Airflow or similar).
• Assist in transitioning legacy datasets and codebases into scalable, cloud-native workflows aligned with our modern data architecture.
• Document data sources, pipeline logic, and data models to ensure maintainability and knowledge transfer.

Qualifications

• Currently pursuing a Bachelor’s or higher degree in Computer Science, Engineering, Management Information Systems, or related technical field.
• Expected graduation date of Winter 2027 or Spring/Summer 2028.
• Strong programming experience in Python (preferred libraries: pandas, NumPy, SQL alchemy, etc.).
• Strong understanding of SQL and experience querying relational databases (Snowflake a plus).
• Exposure to or interest in cloud platforms (e.g., AWS, Azure), particularly with cloud data storage and compute.
• Familiarity with web scraping frameworks and handling large-scale structured and unstructured data sources.