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Staff Software Engineer (Apache Spark Poweruser / Committer)
Apple
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Seattle, United States
Location
Seattle
Posted
June 15, 2026
Commute
Local Area
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This job is in your area. Enjoy a short commute and work close to home.
Job Description
**Weekly Hours:** 40
**Role Number:** 200655487-3337
**Summary**
Seeking extraordinary software engineers with deep experience in scalable batch and streaming processing systems. You will have a passion to push the limits of distributed computing frameworks to get every ounce of performance out of them. Looking for engineers with in depth knowledge of Spark and other related existing frameworks/systems such as Iceberg, Parquet. Also someone who will be passionate by the prospect of working reciprocally with other groups internal to Apple and also communities outside Apple.
**Description**
As an engineer on our team, you will advance our data infrastructure, driving innovation by implementing cutting-edge capabilities and tools that will power Apple Services Engineering. Youβll collaborate closely with a dedicated team of open source data experts (including Spark, Kafka, Iceberg committers amongst others) to enhance and automate our infrastructure, ensuring ...
**Role Number:** 200655487-3337
**Summary**
Seeking extraordinary software engineers with deep experience in scalable batch and streaming processing systems. You will have a passion to push the limits of distributed computing frameworks to get every ounce of performance out of them. Looking for engineers with in depth knowledge of Spark and other related existing frameworks/systems such as Iceberg, Parquet. Also someone who will be passionate by the prospect of working reciprocally with other groups internal to Apple and also communities outside Apple.
**Description**
As an engineer on our team, you will advance our data infrastructure, driving innovation by implementing cutting-edge capabilities and tools that will power Apple Services Engineering. Youβll collaborate closely with a dedicated team of open source data experts (including Spark, Kafka, Iceberg committers amongst others) to enhance and automate our infrastructure, ensuring ...