You know how every investment team says "data is everything"? At this firm, that's not a talking point. It's literally the job. You'd be the person making sure the data layer actually works.
This is a hands on engineering seat at a technology driven investment firm in San Francisco. You'll own the plumbing: the pipelines, the schemas, the infrastructure that the entire research and investing operation runs on top of. Think of it as building the engine room for a ship full of quant researchers and data scientists who need clean, fast, reliable data to do their work.
Day to day, you'll be designing ingestion pipelines that pull from a variety of third party sources, wrangling both structured and messy unstructured datasets, and shipping features that make internal teams faster and more productive.
You'll sit at the intersection of engineering and research, part builder, part thought partner. One week you might be rearchitecting a schema with a data scientist. The next you're debugging a production pipeline or evaluating a new orchestration tool.
The stack is modern and opinionated: Python, SQL, Trino, Apache Iceberg, Polars, Spark, Dagster, and Ray all make appearances depending on the problem. You won't be stuck maintaining legacy systems. There's real greenfield work here.
This is a five days in office role in San Francisco. They want someone who's physically present and embedded with the team.
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