Data Platform Engineer

We are seeking an experienced Data Platform Engineer to join our Storage Analytics team. You will design and build data solutions that provide critical insights into storage performance and usage across Apple's entire device ecosystem.

Description
Working with large-scale telemetry data from millions of Apple devices worldwide, you'll support multiple CoreOS Storage teams, including Software Update, Backup/Restore/Migration, Storage Attribution, and other storage domains.","responsibilities":"Design, build, and maintain scalable data processing infrastructure to handle large-scale telemetry from Apple's global device fleet
Develop highly scalable data pipelines to ingest and process storage performance metrics, usage patterns, and system telemetry with actionable alerting and anomaly detection
Build and maintain robust data platforms and ETL frameworks that enable CoreOS Storage teams to access, process, and derive insights from storage telemetry data
Engineer automated data delivery systems and APIs that serve processed storage metrics to various engineering teams across different storage domains

Preferred Qualifications
Master's or PhD in Computer Science or related field

Deep expertise in data principles, data architecture, and data modeling

Strong problem-solving skills and meticulous attention to detail, with the ability to tackle loosely
defined problem

Minimum Qualifications
Bachelor's degree in Computer Science or related technical field

4+ years of professional experience in data modeling, pipeline development, and software
engineering

Programming Languages: excellent programming skills in Python with strong computer science foundations (data structures, low-level parallelization.

Database Management: Strong SQL skills and hands-on experience with relational databases and query engines (PostgreSQL, Impala, Trino)

Experience with data analysis tools and libraries (Pandas/Polars, NumPy, dbt)

Experience with big data technologies (Kafka, Spark, Databricks, S3)

Experience with Apache Airflow, Dagster, or similar data orchestration frameworks for workflow orchestration, scheduling, and monitoring

Experience with containerization and orchestration (Docker, Kubernetes /visualization & Reporting:

Strong proficiency with creating and maintaining Tableau/Grafana dashboards and workflows","internalDetails":null,"eeoContent":null