Data Engineering Internship (Summer 2026)

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 2026 or Spring / Summer 2027.

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.

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