Lead Data Lakehouse Platform Engineer

Socket.dev; Seattle (WA); On-site; USD 160,000 - 260,000; Full time

Job summary

Apple's Data Platform Data Lakehouse team in Seattle is seeking an experienced engineer to lead the data lakehouse program and mentor teammates. You will drive technical and professional growth while delivering scalable data infrastructure.

You will collaborate with cross-functional partners to plan, implement, and operate services built on Apache Spark, Kafka, Flink, Iceberg, and Iceberg Rest Catalog, running on Kubernetes/EKS to support analytics and ML workloads across Apple.

Qualifications

• 10+ years of experience in design and development of scaling, and operation of distributed systems.
• Proficient in Java or Scala.
• Proficient in Apache Iceberg and Iceberg Rest Catalog specification.
• Designing and developing scalable, reliable APIs.
• Hands-on approach with willingness to engage in daily technical work.
• Open-Source contributions are a plus.
• Strong debugging skills in large-scale distributed systems.
• Exceptional communication and collaboration across teams.

Responsibilities

• Lead the data lakehouse team, guiding team members in technical and professional growth.
• Collaborate with cross-functional teams to plan, execute, and deliver technical projects.

Skills

Distributed systems design

Java/Scala proficiency

Iceberg Rest Catalog

API design

Open‑Source contributions

Debugging large‑scale systems

Communication & collaboration

Cross‑functional leadership

Education

Bachelor's, Master’s, or Ph.D. in CS or related field

Tools

Kubernetes

AWS EKS

Job description

Apple's Data Platform Data Lakehouse team in Seattle is seeking an experienced engineer to lead the data lakehouse program and mentor teammates. You will drive technical and professional growth while delivering scalable data infrastructure.

You will collaborate with cross-functional partners to plan, implement, and operate services built on Apache Spark, Kafka, Flink, Iceberg, and Iceberg Rest Catalog, running on Kubernetes/EKS to support analytics and ML workloads across Apple.