Data Engineer: Scalable Ads Data Pipelines

Apple Inc.; Austin (TX); On-site; USD 150,000 - 278,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Employee stock programs

Job summary

Apple Inc. is seeking a Software Engineer for Apple Ads data engineering to design, develop, and operate scalable data pipelines across batch, near-real-time, and streaming environments.

You will work with Spark, Kafka, and cloud storage to ensure data correctness, privacy, and performance. The ideal candidate will own end-to-end data systems, collaborate with cross-functional teams, and contribute to production-quality software and observability.

Qualifications

• 3+ years of professional software or data engineering experience building production systems.
• Strong CS fundamentals, including data structures, algorithms, concurrency, and distributed systems concepts.
• Strong programming skills in Java and/or Scala, with experience writing production-quality software.
• Hands-on experience building and operating large-scale data pipelines using Apache Spark.
• Strong SQL skills and experience working with large analytical datasets.
• Experience with technologies such as Kafka, Hadoop, S3/object storage, or equivalent large-scale data infrastructure.
• Experience with distributed systems and data processing technologies (e.g. Spark, Kafka, Flink).
• Understanding of data modeling, partitioning strategies, schema evolution, and Parquet.

Responsibilities

• Design, develop, and operate large-scale distributed data processing pipelines using Apache Spark and related big-data technologies.
• Build reliable batch, near-real-time, and streaming pipelines for processing high-volume advertising and measurement data.
• Develop production-quality software primarily using Java, Scala, and/or Python.
• Design scalable data architectures for processing and storing very large datasets.
• Build pipelines using Spark, Kafka, S3/object storage, Apache Iceberg, Hadoop, and cloud-native infrastructure.
• Develop efficient data transformations, aggregations, joins, and data-processing algorithms over large datasets.
• Analyze and optimize Spark applications for performance, memory utilization, shuffle efficiency, parallelism, and compute cost.
• Design systems that gracefully handle late-arriving data, retries, partial failures, reprocessing, and evolving data schemas.
• Build strong data-quality controls, validation mechanisms, reconciliation frameworks, and monitoring to ensure correctness.
• Design systems with privacy, security, and appropriate data-handling principles built into the architecture.
• Develop observability, metrics, alerting, and debugging capabilities for production data pipelines.
• Investigate and resolve complex issues across distributed compute, storage, orchestration, and downstream data systems.
• Participate in architecture and design reviews and contribute to technical decisions for evolving the data platform.
• Write clean, maintainable, well-tested code and participate actively in code reviews.
• Own services and pipelines through their complete lifecycle, including design, development, deployment, monitoring, and production support.
• Collaborate with cross-functional engineering and product teams to deliver scalable solutions for Apple Ads.

Skills

Apache Spark

Java/Scala

Kafka

Python

Distributed systems

SQL

Cloud storage

Data modeling

Hadoop

Kubernetes

Education

Bachelor’s degree in Computer Science or related field

Tools

Apache Spark

Kafka

Hadoop

S3

Apache Iceberg

Kubernetes

Job description

Apple Inc. is seeking a Software Engineer for Apple Ads data engineering to design, develop, and operate scalable data pipelines across batch, near-real-time, and streaming environments.

You will work with Spark, Kafka, and cloud storage to ensure data correctness, privacy, and performance. The ideal candidate will own end-to-end data systems, collaborate with cross-functional teams, and contribute to production-quality software and observability.