About Grasshopper

Grasshopper is a quantitative trading technology provider based in Singapore, and is the holding company of Grasshopper Asset Management. Our state-of-the-art technology, built from the ground up in-house, puts us at the forefront of developments in electronic trading. An unbroken record of consistency and profitability is underpinned by firm values of curiosity, empowerment, and flexibility.

About the Role

We use data to make decisions. Our trading and middle- and back-office teams depend on a platform built with Prefect, dbt, BigQuery, and Looker, and on the engineers who keep it fast, correct and trusted.

We are looking for an Analytics Engineer with strong hands-on engineering skills. Current work includes an ingestion framework for hundreds of data files that arrive every day from brokers and vendors, pipelines that keep our reference data in sync with third-party sources, and the treasury reporting and reconciliation dashboards that our business relies on.

Looking further ahead, we are building toward a platform where anyone can ask a question and trust the answer, whether it comes from a dashboard or a chat window. You will help us put AI to work for the teams we build for.

Technical skills alone are not enough. The problems here get defined by talking to traders, risk managers and financial controllers, and the people who do well are the ones who can sit with a team, learn how they work, turn that into a data product and get it adopted.

Nobody here is equally strong at both, and we do not expect you to be. If you have the engineering depth and want to build the business side, we would like to hear from you.

What We Are Looking For

Must Have:

• Several years building and owning data pipelines in production.
• Comfortable working directly with non-technical teams — asking questions, sitting through their process, and turning a vague ask into something concrete.
• Strong SQL and Python — the kind of code other people can maintain.
• Hands-on experience with an orchestration tool and dbt or equivalent.
• Care about correctness — testing thoroughly, and catching problems before they reach production.
• An eye for user experience — a correct dashboard nobody can read is not finished.

Nice to have:

• A background in financial services, working with trade, position or P&L data
• Cloud platform experience, ideally GCP
• Looker and LookML.
• Working with time series data at scale, ideally ClickHouse
• Integrating AI into existing workflows
• Exposure to a metrics or semantic layer, or reverse ETL.