Data Engineer: market
A Data Engineer builds data pipelines: ingests data from sources, cleans and models it and delivers it to the warehouse that analysts, BI and ML work from. We currently track 5 881 open positions for this role, 5 612 of them fresh. The baseline is SQL and Python, an orchestrator (Airflow, Dagster), a warehouse or lakehouse (Snowflake, BigQuery, Databricks), Spark for large volumes and dbt for models. By co-occurrence in requirements, Python, SQL, AWS and Azure appear most often. 33% of the postings allow fully remote work. Below is a live slice of the Data Engineer market: geography, seniority, adjacent stack and sources.
The Data Engineer market currently has 5,881 open roles, 5,612 of them freshly observed. Median salary $7,355/mo.
33% of Data Engineer postings allow fully remote work; the share counts only postings that state the format.
⚠ salary known for 555 of 5881 jobs; remote share from 4875 with a stated format; 5612 counted as fresh observations; trend and hiring difficulty are not shown
Timeline: postings and sources
How many Data Engineer postings appeared each week since 4 May, and from how many sources. The second line separates market growth from coverage growth: a jump in the week new sources were connected means we started seeing more, not that the market grew.
New postings and active sources per week
Sources over the period: 253
New sources connected: 11 May +10 · 18 May +5 · 25 May +5 · 1 Jun +11 · 8 Jun +2 · 15 Jun +4 · 22 Jun +19 · 29 Jun +46 · 6 Jul +26 · 13 Jul +20 · 20 Jul +19 · 27 Jul +7 · 3 Aug +10 · 10 Aug +5 · 17 Aug +3 · 24 Aug +2 · 31 Aug +8 · 7 Sept +3 · 14 Sept +4 · 21 Sept +7 · 28 Sept +6 · 5 Oct +4 · 12 Oct +6
Week = posting first-seen date, all statuses; postings are selected by the same rule as this page's counter. Sources are distinct collection channels; their names are not published.
Salaries over time
Median Data Engineer salary per week, USD per month.
Median salary, USD per month
Only postings with a USD salary and a known period (month or year), $500–$50,000 per month. Weeks with fewer than 10 such postings are left blank — that means no data, not zero.
Remote work over time
Share of Data Engineer postings offering fully remote work, per week.
Remote postings, %
The share is among postings that state a format (remote, hybrid, office). Weeks with fewer than 10 such postings are left blank.
Technologies over time
How the share of Data Engineer postings mentioning each of the top technologies changed.
Postings mentioning the technology, %
Share among postings with a tagged stack; the series starts on 10 Aug: earlier stack tags were assigned differently. Weeks with fewer than 20 tagged postings are left blank.
Countries over time
How the share of Data Engineer postings in each of the top countries changed, per week.
Postings in the country, %
Share among postings with a known country; the chart shows the five countries with the most postings over six months. Weeks with fewer than 20 postings with a known country are left blank. A rising share can mean a newly connected source in that country rather than market growth.
Demand and observed supply: Data Engineer
| Open demand | 5,881 |
| Observed supply | — not published |
⚠ candidates matching a vacancy are not counted yet: demand and the observed pool are shown
Salary distribution: Data Engineer
One in ten earns under $4,200, one in ten over $15,208. Half the market falls between $5,525 and $11,816. Sample: 555.
The range histogram for Data Engineer uses only postings with an explicit compensation range; the median is computed over the same sample.
Demand geography: Data Engineer
| country | jobs |
|---|---|
| US | 1,039 |
| PL | 823 |
| GB | 562 |
| IN | 405 |
| SG | 341 |
| DE | 248 |
| CA | 157 |
| FR | 136 |
| ZA | 85 |
| RU | 76 |
The top country for Data Engineer demand is the US (1 039 positions).
⚠ job counts only: salary by country is not published
Used together with
In Data Engineer requirements the most frequently named skills and technologies are Python, SQL, AWS and Azure.
Demand by grade: Data Engineer
| grade | jobs |
|---|---|
| senior | 2,175 |
| lead | 324 |
| middle | 319 |
| principal | 288 |
| junior | 157 |
Senior-and-above is about 85% of 3 263 Data Engineer postings with an explicit grade.
⚠ demand side only: the grade of the observed pool is unknown for most of it
Employers: Data Engineer
Demand is spread across 2,667 employers. The largest accounts for 2.3%, the top ten for 8.4%; the remaining 91.6% is long tail.
| share | value |
|---|---|
| top-1 | 2.3% |
| top-3 | 4.3% |
| top-10 | 8.4% |
| long tail | 91.6% |
Data Engineer openings come from 2 667 distinct employers; the largest one accounts for only 2.3% of postings — the market is not tied to a single hirer.
⚠ names are not shown: staffing agencies and end employers are not yet told apart by the classifier
Where Zorky sees this market
Observed across 126 sources; the largest accounts for 13.8% — this market does not rest on a single channel.
Data Engineer postings arrive mostly from ATS & career sites and job boards & aggregators.
Recent openings: Data Engineer
- Data Engineer V - US · US · $13,819
- Azure Data Engineer (Fabric & Cloud Data Platform) · GB · $6,418
- Hyperion Lead, Data Engineering - Night Shift
- Senior Data Engineer with Python and Databricks · RO
- Senior Data Engineer with Python and Databricks · RO
- [VKS] Data Engineer (Mid/Senior) · PL
- Data Engineer · US
- Data Engineering Lead · PL
Adjacent markets
⚠ adjacent markets for comparison are not defined yet
How this is measured
- Vacancy
- an open job that cleared the quality gate and lists at least two technologies
- Observed candidate
- a candidate whose stack contains this technology; an aggregate — not a single record leaves the perimeter
- Matchable candidate
- not counted yet
- Window
- jobs open at the moment the snapshot was built
About the data
- Some breakdowns are hidden: their data coverage is not yet sufficient.
- Statistics are shown only where the sample clears a quality gate.
- A missing block does not mean a value of zero.
Breakdowns currently hidden: 8.
Data as of 2026-10-23
Frequently asked questions
Common questions about the Data Engineer role — short answers from the same data slice.
What does a Data Engineer do?
A Data Engineer builds data pipelines: ingests data from sources, cleans and models it and delivers it to the warehouse that analysts, BI and ML work from.
Which skills do Data Engineer postings require?
The baseline is SQL and Python, an orchestrator (Airflow, Dagster), a warehouse or lakehouse (Snowflake, BigQuery, Databricks), Spark for large volumes and dbt for models. In the current slice, Python, SQL, AWS and Azure appear in requirements most often.
How does a Data Engineer differ from a Data Scientist?
A Data Engineer makes sure data is available, fresh and correct; a Data Scientist builds models and research on top of it. The first cares about pipeline reliability, the second — statistics and ML.
How remote-friendly are Data Engineer jobs?
33% of postings with an explicit format allow fully remote work; the slice tracks 5 881 open positions.
Get the full Data Engineer market details
Full role analytics — salary bands, employers, trends and available candidates. Leave a contact and we'll send the details.