M Science is seeking a Data Engineer Intern to assist in building and maintaining scalable data pipelines and workflows, supporting the design and optimization of data storage and retrieval systems, and processing structured and unstructured datasets using cloud-based technologies to uncover new insights from alternative data for leading financial institutions and corporations.
Requirements
- Experience with Python (data processing libraries such as Pandas, PySpark a plus).
- Knowledge of SQL and basic query optimization.
- Familiarity with cloud computing platforms (AWS, Azure, or GCP).
- Exposure to big data tools (Databricks, Spark).
- Familiarity with data modeling concepts (star schema, dimensional modeling).
- Experience with version control (Git) or CI/CD workflows.
Responsibilities
- Assist in building and maintaining scalable data pipelines and workflows.
- Support the design and optimization of data storage and retrieval systems.
- Work with cloud-based technologies (AWS, Databricks, Snowflake) to process structured and unstructured datasets.
- Help implement data quality checks, testing frameworks, and validation processes.
- Collaborate with engineers, analysts, and researchers to translate business questions into technical solutions.
- Explore and prototype new tools or methodologies to improve efficiency in data processing.
Other
- Anticipated to graduate in May 2027
- Strong analytical and problem-solving skills.
- Curiosity, eagerness to learn, and ability to work both independently and in teams.
- Interest in financial services, fintech, or alternative data research.
