Spark: mercado
Apache Spark is the main engine for distributed big-data processing: batch pipelines, streaming, SQL over the data lake and ML feature preparation. We track 2 556 open positions listing Spark, 2 405 of them fresh. Spark is most often required of data engineers through PySpark; Databricks and cloud services (EMR, Dataproc, Synapse) made it the standard of lakehouse platforms. Most of the demand comes from Data, ML/AI and Backend roles. It most often appears next to Python, SQL and Databricks. 36% of the postings allow fully remote work. Below is measured Spark demand.
El mercado de Spark tiene ahora 2556 puestos abiertos, 2405 de ellos observados recientemente. Median salary $7541/mo. Observed candidate pool — 436.
36% of Spark postings allow fully remote work; the share counts only postings that state the work format.
⚠ salary known for 245 of 2556 jobs; remote share from 2071 with a stated format; 2405 counted as fresh observations; trend and hiring difficulty are not shown
Demanda y oferta observada
| Demanda abierta | 2556 |
| Oferta observada | 436 |
⚠ candidates matching a vacancy are not counted yet: demand and the observed pool are shown
Distribución de salarios
Uno de cada diez gana menos de $4312, uno de cada diez más de $17.583. La mitad del mercado está entre $5989 y $14.166. Muestra: 245.
The range histogram for Spark postings uses only postings with an explicit compensation range; the median is computed over the same sample.
Geografía de la demanda
| país | empleos |
|---|---|
| US | 718 |
| PL | 355 |
| IN | 217 |
| GB | 157 |
| CA | 74 |
| DE | 74 |
| RU | 73 |
| BR | 45 |
| SG | 34 |
| HK | 34 |
The top country for Spark demand is the US (718 positions).
⚠ job counts only: salary by country is not published
Se usa junto con
Spark most often appears next to Python, SQL and Databricks. Databricks among the neighbours is the most common environment Spark runs in today.
Roles que la usan
| rol | empleos |
|---|---|
| Data | 1414 |
| ML/AI | 304 |
| Backend | 112 |
| DevOps | 74 |
| Architect | 68 |
| Fullstack | 61 |
| Analytics Engineer | 46 |
| AI Engineer | 43 |
| Platform Engineer | 34 |
| Product | 34 |
⚠ the `Other` and `IT` buckets are excluded as non-roles
Demanda por nivel
| nivel | empleos |
|---|---|
| senior | 858 |
| principal | 179 |
| lead | 157 |
| middle | 136 |
| junior | 57 |
Senior-and-above is about 86% of 1 387 graded Spark postings.
⚠ demand side only: the grade of the observed pool is unknown for most of it
Empleadores
La demanda se reparte entre 1073 empleadores. El mayor concentra el 2.3%, los diez primeros el 13.1%; el 86.9% restante es cola larga.
| proporción | valor |
|---|---|
| top-1 | 2.3% |
| top-3 | 5.4% |
| top-10 | 13.1% |
| cola larga | 86.9% |
⚠ names are not shown: staffing agencies and end employers are not yet told apart by the classifier
Dónde ve Zorky este mercado
Observado en 106 fuentes; la mayor concentra el 26.3%: este mercado no depende de un solo canal.
Spark postings arrive mostly from ATS & career sites and job boards & aggregators.
Vacantes recientes
- Staff Software Engineer - Ingestion · US
- Xpert: Senior Java/Scala Engineer · ZA
- Analytics Solutions Manager · US
- Data Analytics Tech Lead (m/f/d) - relocation · US
- Manager Software Engineer · IN
- Sr. Staff Software Engineer, Systems Infrastructure - Observability Streaming · IN
- Data Engineer (KTV3W) · TH
- Data Engineer - Java & Spark (f/m/x) · PL
Mercados adyacentes
⚠ adjacent markets for comparison are not defined yet
Cómo se mide
- Vacante
- an open job that cleared the quality gate and lists at least two technologies
- Candidato observado
- a candidate whose stack contains this technology; an aggregate — not a single record leaves the perimeter
- Candidato emparejable
- not counted yet
- Ventana
- jobs open at the moment the snapshot was built
Sobre los datos
- Algunos desgloses están ocultos: su cobertura de datos aún no es suficiente.
- Las estadísticas se muestran solo donde la muestra supera un control de calidad.
- Que falte un bloque no significa que el valor sea cero.
Desgloses ocultos actualmente: 7.
Datos a 2026-10-26
Preguntas frecuentes
Common questions about the Spark market — short answers from the same data slice.
What is asked about Spark in a data-engineer interview?
Lazy evaluation and execution plans, partitioning and shuffle, broadcast joins, handling data skew, caching, storage formats (Parquet, Delta), Structured Streaming.
PySpark or Scala for Spark?
PySpark is noticeably more common on the market — it is part of the standard data-engineer toolkit. Scala appears in teams where performance matters and custom extensions are written.
How big is the Spark market?
The slice tracks 2 556 open positions listing Spark; Spark rarely appears in the job title — it is part of the data-engineer, ML-engineer and data-architect profile.