Apache Spark and Big Data AI Jobs (2026)
Apache Spark remains the standard for large-scale data processing in AI and ML pipelines. These positions require expertise in distributed computing, PySpark, Spark ML, and building data processing systems that feed machine learning models with high-quality data at scale.
Last updated: June 27, 2026
Latest Apache Spark AI Jobs
View all jobsBig Data Scientist for the Services Analytics Plateau
Data Engineer/Big Data Engineer (Middle)
Big Data Engineer
Big Data Engineer (Cancer Science Institute)
Java Backend Engineer (Spring boot, Cloud, AI/Big Data) - Treasury Management Systems
AI / Data Engineer Senior (Python, PySpark, AWS)
Software & Big Data Engineer
Data Engineer - Big Data
Big Data Engineer
Staff Software Engineer - Java/Agentic AI/Big Data
Manager - Tech Solutions (Big Data / AI)
Data Engineer (Python/Spark)
Data Engineer (Python/Spark)
Director,Technical Solutions (Big Data/ AI)
[Job -29790] Senior Data Engineer | (Spark + Databricks)
[Job -29790] Senior Data Engineer | (Spark + Databricks) Hybrid Setup
Core Data - Big Data Engineer
Senior Big Data Engineer (R-19335)
Senior Data Engineer, Python, Spark
Senior Data Engineer, Python, Spark
Frequently Asked Questions
Is Spark still relevant for AI in 2026?
Yes. Apache Spark is widely used for large-scale data preparation, feature engineering, and batch ML processing. While deep learning training uses GPU frameworks, Spark handles the upstream data processing that feeds ML pipelines. Databricks Spark, PySpark, and Spark Structured Streaming are widely used.
What Spark skills are in demand?
Key skills include PySpark, Spark SQL, Spark Structured Streaming, Delta Lake, data lakehouse architecture, and integration with ML frameworks. Experience with Databricks, AWS EMR, or Google Dataproc is highly valued.
AI Job Insights for Apache Spark AI Jobs
Salary Range (Yearly, USD)
$60K - $481K
Median $143K from 76 listings with salary data
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