WHO WE’RE LOOKING FOR

• A Python expert who writes clean, fast, maintainable code (think Pandas, NumPy, async/await, multiprocessing).
• Someone who’s obsessed with data quality—you notice edge cases before they become problems.
• A pragmatic builder who can take a vague research ask and turn it into a scalable pipeline.
• Experience with cloud infra (AWS/GCP), schedulers, and CI/CD—you know how to ship robust systems.
• Bonus points if you’ve worked with financial/time-series data or have a quantitative background.

THE ROLE IN A NUTSHELL

You’ll be the go-to problem solver for quant researchers, ensuring they have clean, structured, and instantly accessible data for modeling. Your work will involve:

• Transforming raw, messy datasets (market data, alternative data, unstructured feeds) into research-ready formats.
• Building high-efficiency pipelines in Python (this is about lean, performant code).
• Creating simulations and tooling that let quants test ideas faster.
• Automating data validation so researchers can trust what they’re working with.

This isn’t a generic data engineering role—you’ll be deep in the trenches with quants, understanding their needs and building solutions that give them an edge.

WHY THIS ROLE?

• Direct impact on trading strategies—your work enables the research behind them.
• Zero bureaucracy around tools—use what makes sense (as long as it’s Python).
• Collaborate with world-class quants who rely on your systems daily.
  If you love solving hard data problems with code, this is your niche.