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: October 2, 2026
Latest Apache Spark AI Jobs
View all jobsSoftware & Big Data Engineer
Senior Machine Learning Engineer, Accelerated Apache Spark
Data Engineer/Big Data Engineer (Middle)
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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)
Senior Big Data Engineer
Senior Data Engineer, Python, Spark
Senior Data Engineer, Python, Spark
Big Data Engineer
Big Data Engineer
Spark Data Engineer
Data Engineer (5 to 7 yrs) (PySpark / Azure / Python / DataBricks) - Remote India
Senior Manager - Technical Solutions (Big Data / AI)
Senior Internal Audit Manager - Big Data and AI Strategy for Internal Audit
ML & Big Data Analyst
Senior Software Engineer - Big Data/ML Ops
Data Engineer with Scala and Spark/ Pyspark
Big Data Engineer 9/9/2026, 9:40:56 AM
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 - $500K
Median $142K from 68 listings with salary data
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