Data Engineer
New York, New York, United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll bring
All qualificationsCore experience
- Proficient with SQL or DataFrame libraries like pandas or Polars
Preferred experience
- Prior experience with financial data is helpful but not required.
Qualification wording
Proficient with SQL or DataFrame libraries like pandas or Polars
Prior experience with financial data is helpful but not required. We’re happy to hire talented engineers and teach them what they need to know.
Tools in this posting
- Python
- SQL
- pandas
- Polars
Source — Tool mentions in context
About You - Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code - Proficient with SQL or DataFrame libraries like pandas or Polars
- Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code - Proficient with SQL or DataFrame libraries like pandas or Polars - Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets
Job description
About the Position
We are looking for a Data Engineer to turn messy, real-world datasets into reliable inputs for research and trading. Jane Street depends on data from a wide variety of sources to understand markets and the global economy—think world news, decades of weather patterns, deidentified credit card spending, or packet captures of stock exchange market data feeds. Clean, well-structured data is the difference between noise and a profitable trading signal.
You'll work closely with trading desks to identify Jane Street's data needs, evaluate datasets, and build pipelines that ingest and transform external data. You'll figure out what data means and how best to represent it. We build our own tools and software when needed, so you'll also help shape the systems you use every day.
This is a collaborative role, but you'll own your work from end to end. It requires a mix of engineering, data analysis, and product sense. You'll develop deep expertise in your data domains and use that understanding to decide what's worth building next.
About You
- Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code
- Proficient with SQL or DataFrame libraries like pandas or Polars
- Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets
- A clear and concise communicator
Prior experience with financial data is helpful but not required. We’re happy to hire talented engineers and teach them what they need to know.
If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on www.janestreet.com. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
New York, New York, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Apr 14, 2026
- Recorded sightings
- 183
- Last seen by us
- Oct 7, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.