Strong SQL and Python skills, used daily for pipeline development, data modelling, and automation.

Experience with modern data stack tooling: a cloud data platform (Databricks preferred), and version control (Git/GitHub).

A solid understanding of data modelling, warehousing patterns, and ETL/ELT design.

To be comfortable working with Postgres or similar relational databases.

Clear communication - you can explain a data model to a fund manager and discuss trade-offs with an engineer.

A bias toward shipping: you’d rather get something working and iterate than spend weeks in design.