Principal Data Engineering Lead - Services Special Project

Apple Inc.; Cupertino (CA); On-site; USD 263,000 - 394,000; Full time

Benefits offered by this job

Employee stock plan

Medical and dental coverage

Retirement benefits

Product discounts

Tuition reimbursement

Relocation assistance

Job summary

Apple Inc. in Cupertino seeks a Principal Data Engineering Lead to drive design, build, and operations of a real-time data platform. You will partner across groups to translate complex data requirements into scalable pipelines that power analytics, billing, and optimization.

The role emphasizes batch and streaming ETL/ELT, Kafka-based ingestion, data modeling, lineage, and governance, with collaboration across ML engineers and platform teams to deliver robust data solutions.

Qualifications

• Masters Degree required.
• 12+ years of data engineering experience with large ETL/ELT pipelines.
• Proficiency in dimensional data modeling for analytics and reporting.
• Experience with SQL/NoSQL databases (Postgres, Cassandra, Redis).
• Strong Spark experience and distributed data processing.
• Proven skills in Scala/Java software engineering.
• Hands-on with Kafka, Iceberg, and Flink.
• Experience with Airflow and Beam workflows.
• Proficient with AWS services (S3, EMR, Lambda, Glue, Redshift).
• Experience with Trino/Presto/Snowflake for analytics.
• Hands-on with big data lake architectures and Kubernetes/Docker.
• Experience deploying ML/LLM pipelines in production.

Responsibilities

• Build batch and streaming ETL/ELT pipelines ingesting diverse data sources.
• Develop Kafka-based ingestion and processing pipelines to data lake.
• Create robust data models optimized for analytics and reporting.
• Define data quality checks, SLAs, and observability standards.
• Integrate raw signals with metadata for downstream analytics and billing.
• Enforce data lineage, metadata management, and schema governance.
• Deliver logging, anomaly detection, validation, cleaning, and transformation pipelines.
• Collaborate with ML engineers, data scientists, platform teams and leadership.
• Advance data stack tooling, frameworks, and operational standards.
• Align with other Apple teams on strategic data initiatives.

Skills

Masters Degree

12+ years experience

Dimensional modeling

SQL/NoSQL

Apache Spark

Big Data platforms

Scala/Java

Apache Kafka

Airflow/Beam

AWS services

Trino/Presto/Snowflake

PySpark

Docker/Kubernetes

LLM/ML model deployment

Education

Masters Degree

Tools

Kafka

Spark

Airflow

Beam

Hadoop

Kubernetes

Jenkins

Python

PySpark

Iceberg

TigerGraph

Job description

Principal Data Engineering Lead - Services Special Project

Cupertino, California, United States Software and Services

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.

Responsibilities

• Build and implement batch and streaming ETL/ELT pipelines that ingest, process, and model data from diverse sources, including unstructured media and real-time event streams, ensuring high reliability, performance, and scalability.
• Develop and maintain Kafka-based ingestion and processing pipelines, ensuring reliable data delivery across services and into the data lake.
• Build robust logical and physical data models with a focus on dimensional modeling, versioning, and storage patterns (e.g., Parquet, ORC) optimized for ingest, reporting, and operational use cases.
• Define and enforce data quality checks, SLAs, and observability standards to ensure data is accurate, timely, versioned, and trusted by stakeholders.
• Integrate and enrich raw signals with metadata and attribution to power downstream use cases such as analytics, billing, planning, and optimization.
• Implement standard methodologies for data lineage, metadata management, schema governance, versioning, and security in alignment with Apple's standards for data protection and privacy.
• Deliver solutions that include logging, anomaly detection, data validation, cleaning, and transformation, with strong emphasis on monitoring, debuggability, and continuous improvement.
• Work closely with ML engineers, data scientists, platform teams, and leadership to translate requirements into scalable, reliable data solutions.
• Help advance the team's data stack, including tooling, frameworks, and standards for development, testing, deployment, and operations.
• Align our team with other Apple teams strategically, participating in larger scale discussions and deliverables across our ecosystem.

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/NoSQL Databases (including Postgres / Cassandra / Redis)
• Strong experience with distributed data processing frameworks including Apache Spark
• Strong experience with Parallel processing frameworks: BigTable/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, BigQuery, Kinesis, or similar services
• Experience with Analytics frameworks including Trino (Presto, BigQuery, 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 PySpark
• Familiarity with graph databases such as TigerGraph
• 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, TorchServe 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)

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $262,500 and $394,000, and your base pay will depend on your skills, qualifications, experience, and location.

• Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.
• Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.
• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses — including tuition.
• This role might be eligible for discretionary bonuses or commission payments as well as relocation.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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. Learn more about your EEO rights as an applicant

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Apple accepts applications to this posting on an ongoing basis.