Software Data Engineer, App Store

Apple Inc

Quick summary

Work type: On-site
Location: San Francisco, CA
Salary: $147,400–$220,900 / yr
Posted: 29 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $182k

This role $184k

$132k most similar roles pay here $237k

This role pays more than 52% of similar roles. Most pay $141,925–$221,175 — the shaded band above. At the midpoint, this role pays about $184k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

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At a glance

TL;DR · Software Data Engineer, App Store

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As a Software Data Engineer on Apple's App Store Data team, you will contribute to shaping strategic initiatives that drive innovation and decision-making for the world’s largest app marketplace. Your responsibilities include designing and building scalable data pipelines with CI/CD, developing data architectures using distributed systems like Spark and Kafka, and implementing monitoring and observability for production systems. You will also clean and transform large-scale datasets into analytics-ready formats using Python, Scala, or Java, and collaborate closely with cross-functional teams to translate requirements into precise data model specifications. Success in this role requires expertise in big data technologies, proficiency in AI coding assistants, and a commitment to privacy and compliance standards, all while working on high-impact projects that enhance the App Store experience for users and developers globally.

Skills

CI/CD Python Scala Java SQL Spark Flink Kafka Airflow Iceberg Trino Kubernetes Hadoop Docker Prometheus Grafana AI coding assistants LLM-augmented workflows

What you'll do

Design and build scalable data pipelines with CI/CD ensuring reliability through tests.
Develop data architectures using distributed systems like Spark and Kafka for high-throughput processing.
Implement monitoring and observability for production data systems to ensure stability.
Clean, transform, and model large-scale data into analytics-ready datasets using Python or Scala.
Contribute to quantitative analysis projects from data quality to statistical analysis and visualization.

What we're looking for

3+ years of experience building production data pipelines on distributed systems
Proficient in Scala, Java, Python, and SQL for data processing and analysis
Hands-on experience with big data technologies like Hadoop, Spark, Kafka, Airflow
Strong knowledge of data modeling, structured/unstructured data analysis, predictive modeling
Active use of AI coding assistants and rigorous code review practices
Excellent communication skills and proven success collaborating across functions

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