4 hours ago
Cupertino, CA, USA +2 moreMid Level
H1B Sponsor
Responsibilities
- Design and implement distributed data pipelines processing large volumes of advertising events across batch, near-real-time, and streaming environments.
- Build, deploy, operate, and provide production support for scalable data processing and reporting infrastructure.
- Optimize Apache Spark workloads, including partitioning, shuffles, joins, caching, execution plans, memory management, and performance.
- Design data models, partitioning strategies, schema evolution approaches, and efficient storage solutions.
- Ensure data correctness, quality, reliability, privacy, scalability, and performance across production systems.
- Build systems supporting replay, backfills, reprocessing, late-arriving data, reconciliation, lineage, and data contracts.
- Collaborate with engineers, product teams, data scientists, SREs, and technical and non-technical partners.
- Own complex projects end-to-end from architecture and implementation through deployment, observability, monitoring, alerting, and operational support.
Requirements
- At least 3 years of professional software engineering or data engineering experience building production systems.
- Strong computer science fundamentals in data structures, algorithms, concurrency, and distributed systems.
- Strong production programming skills in Java and/or Scala.
- Hands-on experience building and operating large-scale data pipelines with Apache Spark.
- Experience designing distributed batch and/or streaming data processing systems.
- Experience with large-scale data infrastructure such as Kafka, Hadoop, and S3 or equivalent technologies.
- Strong SQL skills and experience working with large analytical datasets.
- Knowledge of distributed data processing technologies such as Spark, Kafka, and Flink.
- Understanding of data modeling, partitioning strategies, schema evolution, and efficient storage formats such as Parquet.
- Experience building reliable production systems with testing, monitoring, alerting, and operational support.
- Strong debugging, problem-solving, communication, and cross-functional collaboration skills.
- Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
- Preferred experience with petabyte-scale data processing systems and deep Apache Spark performance tuning.
- Preferred experience with Apache Iceberg, AWS technologies including S3, Kubernetes/EKS, and containerized distributed workloads.
- Preferred familiarity with analytical data stores and query engines such as Druid and Trino.
- Preferred experience building reusable data platforms or processing frameworks and privacy-preserving data systems.
- Preferred experience with advertising, measurement, reporting, analytics, data-quality, reconciliation, lineage, or data-contract frameworks.
Tech Stack
Categories
Data Engineering
About Apple
We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. And the same innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it. This is where your work can make a difference in people’s lives. Including your own. Apple is an equal opportunity employer that is committed to inclusion and diversity. Visit apple.com/careers to learn more.