Data Engineer

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 mid level role in BELTO Ventures. 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 batch and streaming pipelines with tested transformations.
• Model warehouse layers for analysis and reporting.
• Implement data quality checks, lineage and alerting on freshness.
• Manage cost and performance of warehouse workloads.
• Document datasets so analysts do not need to ask you.

• Production data engineering with SQL and Python.
• Experience with a modern warehouse and orchestration tooling.
• Understanding of dimensional modelling and its trade-offs.
• Ownership of data correctness end to end.
• Currently enrolled at, or holding a degree from, 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.