Principal Data Engineering Lead - Services Special Project

** Weekly

Hours:

** 40

** Role Number:*
* ** Summary*
* At Apple, great ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Our team is building a massive, real-time platform that transforms continuous streams of multimodal data (including structured, image, and log data) into an intelligent, searchable foundation.

We are seeking a Principal Data Engineer to lead and drive not only our team's data processing systems, but also to partner at a larger scale, coordinating and synching strategically with other business groups and organizations within Apple.

** Description*
* We are seeking a Principal Data Engineering Lead with deep expertise in ETL/ELT, data architecture, and applied ML pipelines to drive the design, build, and operations of this infrastructure. As a key member of our team, you will be responsible for driving critical decisions and operations across the entire system while aligning strategically across Apple.

** Minimum Qualifications*
* + Masters Degree

+ 12+ years of experience in data engineering, including building and maintaining large-scale ETL/ELT data pipelines

+ Proficiency in data modeling, especially dimensional modeling, and designing schemas optimized for analytics and reporting

+

Experience with leveraging databases including SQL/No

SQL Databases (including Postgres / Cassandra / Redis)

+ Strong experience with distributed data processing frameworks including Apache Spark

+ Strong experience with Parallel processing frameworks:
Big Table/Hadoop

+ Strong software engineering fundamentals and proven experience with Scala, Java

+ Hands-on experience with Apache Kafka, Iceberg, and Flink.

+

Experience with workflow orchestration tools including Apache Airflow and Beam

+

Experience with AWS:  e.g., S3, EMR, Lambda, Glue, Redshift, Big Query, Kinesis, or similar services

+

Experience with Analytics frameworks including Trino (Presto, Big Query, Snowflake)

+ Hands-on experience with big data lake architectures

+

Experience with containerization and orchestration (Docker, Kubernetes/EKS) and CI/CD tooling including Jenkins

+ Experience in Python and Py Spark

+ Familiarity with graph databases such as Tiger Graph

+ Experience building pipelines that process multimodal data (structured and image) and integrate ML model inference - including LLMs and embedding models - for data enrichment and transformation

+ Hands-on experience deploying, serving, and optimizing LLMs or ML models directly in the production, inference runtimes/compilers (ONNX Runtime, TensorRT/TensorRT-LLM), and serving frameworks (Triton, vLLM, Torch Serve or similar).

+ Experience tuning batching, KV-cache, and GPU utilization for low-latency, high-throughput real-time inference in a data pipeline

+ Knowledge of data governance principles, data security best practices, and data privacy regulations

+ Proven experience delivering a consumer-oriented solution by participating at every stage of the development life-cycle.

+ Excellent communication skills and a collaborative mindset with past experience presenting and partnering with VP and C level decision makers.

** Preferred Qualifications*
* +

Experience with data versioning tools and frameworks (e.g., DVC, Delta Lake)

+ Experience storing/serving embeddings (e.g., pgvector, Milvus, FAISS)

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.