Neuronify

Data pipelines (ETL)

The jobs that move data from where it is created to where it is used, cleaning and reshaping it on the way. Every AI system sits on top of one.

Hiring data as of September 20, 2026 · refreshed daily

companies naming it
30 of 47companies naming it
open roles naming it
73open roles naming it
of those based in NYC
51of those based in NYC
median posted base (n=42)
$213kmedian posted base (n=42)

What Data pipelines means

A data pipeline extracts data from source systems, transforms it into a usable shape, and loads it somewhere it can be queried or fed to a model. ETL and ELT name the two common orderings of those steps. Orchestrators such as Airflow and Dagster schedule the work; tools such as dbt define the transformations.

AI projects fail on data more often than on models. A retrieval system is only as good as the documents that were ingested, and an agent acting on a stale or inconsistent record will be wrong with full confidence.

Data pipelines in New York job posts

30 of the 47 New York AI companies we track name Data pipelines in at least one open role today, across 73 postings. 51 of those are based in New York; the rest are remote or in the companies’ other offices.

This is engineering vocabulary: 77% of the postings that name it are Engineering roles.

How to read it

Named across a wide set of companies and not only in data-engineering roles: forward-deployed engineers, in particular, are expected to build the pipelines that connect a customer’s systems to the product. If you come from data engineering, this is the most direct bridge into an AI company.

What these roles pay

$190k25th percentile
$213kMedian
$247k75th percentile

Midpoints of 42 distinct salary ranges posted on New York roles that name Data pipelines. Base salary only; on-target earnings are excluded, and a range repeated across one company’s postings counts once. For comparison, the median across all New York engineering postings is $215k. A term’s pay reflects the roles that name it as much as the skill itself — see the role mix below before reading a premium into it. Full bands by function and seniority are in the NYC salary calculator.

Trend

We began extracting this term from posting text on September 20, 2026. Job descriptions disappear when a role is filled, so the series cannot be backfilled; a trend line appears here once a week of data exists.

Who names it

Open roles naming Data pipelines, by company.

Also: Hebbia, Modal, Patlytics, Preql, Runway, Spade, Tennr, Vic.ai, Anterior, April, DataKind, Grow Therapy, Hume AI, Mirage (fka Captions), Norm Ai, Normal Computing, Pinecone, Rillet.

Which roles

The same postings, by function and by seniority.

  • Engineering56
  • GTM5
  • Other4
  • Research4
  • Operations2
  • Product1
  • Mid36
  • Senior17
  • Staff/Principal14
  • Manager3
  • Director2
  • Entry1

Named alongside Data pipelines

Terms that appear in the same postings far more often than chance would put them there. The number is how many of the 30 companies pair the two.

Open roles naming Data pipelines

A sample from today’s data, New York roles first and one per company before any repeats. Links go to the employer’s own posting. For the full market, see AI jobs in NYC.

On the AI in NYC Show

How this is counted

Every day we read the open roles on the public job boards of the New York AI companies in our coverage — the NYC AI 100 and the AI in NYC Show roster. This term is matched against each role’s description after removing the text a company repeats across its postings, so an “About us” paragraph cannot tag every role the company has open. A vendor’s own postings never count toward its own name.

The figure means named in a job posting. It does not mean used in production, and a “nice to have” counts the same as a requirement. Companies are the headline number because posting counts are dominated by whichever few employers are hiring hardest this month.

Full method, including the pay rules, is on the glossary index; the underlying series is the NYC AI Hiring Index.

Data pipelines — common questions

What does Data pipelines mean in an AI job posting?

The jobs that move data from where it is created to where it is used, cleaning and reshaping it on the way. Every AI system sits on top of one. Named across a wide set of companies and not only in data-engineering roles: forward-deployed engineers, in particular, are expected to build the pipelines that connect a customer’s systems to the product. If you come from data engineering, this is the most direct bridge into an AI company.

How many New York AI companies are hiring for Data pipelines?

As of September 20, 2026, 30 of the 47 New York AI companies we track name Data pipelines in the description of at least one open role, across 73 postings (51 based in New York). The count refreshes daily from the companies’ own job boards.

What do roles that ask for Data pipelines pay in New York?

Across 42 distinct posted salary ranges on New York roles naming Data pipelines, the median midpoint is $213k base, with the middle half between $190k and $247k. The same figure for all New York engineering postings is $215k. These are employer-posted ranges required by New York’s pay transparency law, base salary only.

Which skills are asked for alongside Data pipelines?

In the same postings, the terms most distinctively paired with Data pipelines are dbt, Apache Kafka, GCP, SQL, Azure. We rank pairings by how much more often they appear together than apart, so near-universal terms such as Python do not crowd out the informative ones.

Need someone who has actually shipped this?

A keyword in a posting is easy to match and hard to verify. We match companies with AI engineers and consultancies vetted on production work, and tell you when the project needs a different skill than the one you named.

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