Data Engineering Intern at M1 Finance
M1 is a young, rapidly growing company revolutionizing personal finance. The current tools used to invest, borrow, or spend your money are woefully undershooting what’s possible -- so we have created a new generation of investment and banking tools that will entirely reinvent how people interact with their money.
Our signature product is a beautiful, one-of-a-kind, free investing platform. People can easily create and automate their investments, borrow against a flexible portfolio line of credit, and soon, use M1 as their bank -- creating a finance experience that is totally new and incredibly exciting. There has never been an easier, more convenient, or less expensive way to control all aspects of your finances.
We manage hundreds of millions of dollars and are signing up thousands of new customers each week. But we are not done! We have ambitious plans to take on an entrenched, aging industry. Join us and help build the future of personal finance.
M1 is looking for an intern to join our Data Engineering team that works with our. Backend Engineers. Our internship will work closely with the team on specific projects that move the company forward. We're looking for a student who can join us over the summer and make a big impact on the product. You'll work closely with a mentor and have the ability to work closely with very talented engineers. This is a paid internship for 40-hours a week, spanning 12 weeks.
As a Data Engineering Intern, you'll:
- Identify valuable new sources of data and integrate them into M1's data lake and data warehouse
- Design and implement data pipelines in Python
- Develop SQL-based workflows for enriching and de-duplicating data
- Collaborating with stakeholders to produce meaningful metrics of data quality
- Create and maintain dashboards and visualizations to communicate critical business metrics to all parts of M1
- Advanced Bachelors student, Masters student, or recent bootcamp grad
- Experience with Python and/or SQL (both preferred)
- Willingness to learn
- Curiosity and Attention to Detail
- Interest in scientific visualization or information design, a plus