Data Engineer Intern

Summer 2027 Data Engineer Intern – Data + AI Location: New York, NY | Hybrid Program Duration: Summer 2027 (10-12 Weeks) (30 hr per week commitment) Looking for applicants anticipated to graduate between December 2027 & May 2028 About M Science M Science helps institutional investors see what is changing across businesses, industries, and consumer behavior—and understand why it matters. Our team turns differentiated data into intelligence that helps investors find signals, monitor investment ideas, and build conviction. M Science gives clients the flexibility to use that intelligence in the way that fits their process: read our research, explore the underlying data through our Unified Data Model, or bring it into AI tools and internal systems through our MCP Server. The Opportunity We are seeking a Data Engineer Intern to join our team for the summer. This internship is designed for students who are passionate about data, technology, and problem-solving. You will gain hands-on experience working with large datasets, building data pipelines, and supporting real-world research initiatives. Interns at M Science work alongside experienced data scientists and engineers to support impactful research used by hedge funds, asset managers, and other institutional clients. Key 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) 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. What You’ll Learn Best practices in ETL/ELT development and pipeline orchestration. Working with big data tools like Spark, Databricks, and Airflow. Fundamentals of data governance, lineage, and quality assurance. Application of SQL and Python to solve real-world data problems. Exposure to financial services research and the use of differentiated data in decision-making. Preferred Qualifications Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field anticipated to graduate between December 2027 and May 2028. Experience with Python (data processing libraries such as PySpark a plus). Knowledge of SQL and basic query optimization. Familiarity with cloud computing platforms (AWS, Azure, or GCP). Strong analytical and problem-solving skills. Curiosity, eagerness to learn, and ability to work both independently and in teams. Nice-to-Have Skills 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. Interest in financial services, fintech, or differentiated data research. Why M Science? Gain hands-on experience in a fast-growing differentiated data and analytics firm. Work directly with senior engineers and analysts on impactful projects. Hybrid work model offering both in-office collaboration and flexibility. A culture that values learning, innovation, and curiosity. Hourly Rate: Up to $45/hr USD