Jane Street · New York, NY

Salary
Posted
Jul 22, 2026
Location
New York, NY
Last confirmed open
Jul 23, 2026

What this job asks for AI summary

This role centers on sourcing, evaluating, and transforming external datasets — ranging from weather records and news to credit card transactions and exchange market data feeds — into clean, reliable inputs for research and trading. The work spans building ingestion pipelines, making sense of unfamiliar data, and contributing to internal tooling. It suits engineers who combine solid coding ability with analytical curiosity and an interest in data quality.

Mid level · New York-Newark-Jersey City, NY-NJ-PA · Full-time

Must have (1)
SQL, pandas or Polars
Nice to have (1)
Python

“or” means any one of them counts — you don't need all of them.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

Roughly 1,950 people in the New York-Newark-Jersey City, NY-NJ-PA area plausibly meet what this posting asks for (database architects). range 1,450–3,050

Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.

What won't set you apart
SQL90%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $134,433 (middle half $95,331–$179,625).

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (6)

The posting names no specific location; Jane Street's primary office is New York, NY, so the CBSA has been inferred accordingly.

Python is listed as 'a plus' in the About You section, making it preferred rather than required.

SQL is listed as a hard requirement, with pandas and Polars offered as alternatives ('SQL or DataFrame libraries like pandas or Polars'). pandas and Polars are also captured separately as preferred since they appear alongside SQL as acceptable alternatives rather than independent requirements.

Financial data experience is explicitly called out as helpful but not required.

The role sits between data pipeline engineering (15-1243) and general software development (15-1252); the emphasis on building ingestion/transformation pipelines and data modeling points to 15-1243 as the primary classification, but the 'build our own tools and software' framing introduces genuine ambiguity.

No experience floor, compensation range, or degree requirement is stated in the posting.

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