Data Engineering Intern

This is an active talent brief for work BELTO may staff as client demand and internal priorities require. Publication does not imply an existing team vacancy or a guaranteed hiring date.

This is a fully remote internship role in BELTO Software Services. You will work with a distributed team on consequential client and internal priorities.

The work combines hands-on delivery, architecture decisions, peer review, documentation and direct collaboration with commercial and delivery colleagues. We value clear reasoning, secure defaults and systems that remain understandable as they scale.

Success means improving the quality and speed of decisions, leaving durable operating assets, and communicating trade-offs before they become surprises. The selection process includes a structured conversation and a practical, role-relevant exercise. We do not use protected personal characteristics in hiring decisions.

• Build and test ingestion and transformation jobs against real specifications.
• Write data quality checks and explain what each one protects against.
• Document datasets, fields and known limitations.
• Investigate pipeline failures and report the cause clearly.
• Present your project and its trade-offs at the end of the internship.

• Python and SQL at a working level.
• Understanding of relational data modelling basics.
• Care about correctness over speed.
• Availability for the full internship period, working remotely.
• Currently enrolled at Stanford University or Harvard University.

Applicants must be currently enrolled at, or hold a degree from, Stanford University or Harvard University. This is a BELTO hiring policy; neither university sponsors, endorses or partners in this recruitment.

Applicants must be currently enrolled at, or hold a degree from, Stanford University or Harvard University. This is an independent BELTO hiring policy; neither university sponsors, endorses or partners in this recruitment.