Data Engineer, Apple Ads

What you'll do

• Design and operate large-scale distributed data processing pipelines using Apache Spark, Kafka, and cloud storage.
• Build reliable batch, near-real-time, and streaming pipelines to process high-volume advertising and measurement data.
• Develop production-quality software for data transformation, aggregation, and complex join operations using Java, Scala, or Python.
• Optimize Spark applications for performance, memory utilization, shuffle efficiency, and reduced compute costs.
• Implement robust data quality controls, validation mechanisms, and reconciliation frameworks to ensure accuracy across the data lifecycle.
• Design systems that handle late-arriving data, retries, partial failures, and evolving data schemas.
• Build observability features including metrics, alerting, and debugging capabilities for production data pipelines.
• Ensure all data architectures incorporate privacy, security, and appropriate handling principles into the core design.

What we're looking for

• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
• 3+ years of professional software engineering or data engineering experience building production systems.
• Strong computer science fundamentals including data structures, algorithms, concurrency, and distributed systems concepts.
• Proficiency in Java and/or Scala to write production-quality software.
• Hands-on experience building and operating large-scale data pipelines using Apache Spark.
• Experience with distributed batch and streaming processing using technologies like Kafka, Hadoop, or Flink.
• Strong SQL skills and experience working with large analytical datasets.
• Expertise in data modeling, partitioning strategies, schema evolution, and efficient storage formats like Parquet.