Sr. Data Engineer - Services Special Projects

Apple Inc.; Cupertino (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Health insurance

Employee stock program

Relocation assistance

Tuition reimbursement

Job summary

Apple Inc. is seeking an experienced Data Engineer in Cupertino to design and operate scalable ETL/ELT pipelines, leveraging multimodal data and ML enrichment. You will build batch and streaming data flows, implement governance and observability, and work with ML teams to translate requirements into robust data solutions.

You will collaborate across data platforms, streaming ingestion, and model inference, shaping a scalable data foundation for analytics, billing, and planning use cases.

Qualifications

• Masters degree in a relevant field (CS/EE/Analytics).
• 10+ years in data engineering with large-scale ETL/ELT pipelines.
• Proficiency in dimensional data modeling and analytics schemas.
• Experience with SQL/NoSQL databases (Postgres/Cassandra/Redis).
• Strong Spark experience and Kafka-based data ingestion.
• Hands-on with Airflow, Docker, Kubernetes/EKS, and CI/CD tooling.
• Experience deploying ML pipelines and ML-enabled data enrichment.
• Familiarity with data governance, security, and privacy practices.

Responsibilities

• Design and build batch and streaming ETL/ELT pipelines at scale.
• Develop Kafka-based ingestion and processing pipelines into the data lake.
• Create robust data models optimized for analytics and reporting.
• Implement data quality checks, SLAs, and observability standards.
• Integrate raw signals with metadata to power downstream use cases.
• Enforce data lineage, schema governance, and security practices.
• Deliver logging, validation, cleaning, and transformation with good monitoring.
• Collaborate with ML engineers, data scientists, and platform teams.
• Advance the data stack with tooling, frameworks, and standards.

Skills

Apache Spark

Apache Kafka

Python

ETL/ELT pipelines

Data modeling

SQL/NoSQL databases

Airflow

Kubernetes

PySpark

AWS

Scala/Java

Delta Lake / Iceberg

ML pipelines / LLMs

DVC

GIT / CI/CD

ONNX Runtime / TensorRT

Education

Masters Degree

Tools

Apache Airflow

Docker

Kubernetes/EKS

Beams: Beam

Jenkins

Trino / Presto / BigQuery

Spark SQL

Flink

Job description

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.By enriching this data with language and embedding models, we power critical experiences for billions of Apple customers across multiple downstream applications.

Description

We are seeking an experienced Data Engineer with deep expertise in ETL/ELT, data architecture, and applied ML pipelines to design, build, and operate this infrastructure. As a key member of the team, you will be responsible for creating the massively scalable pipelines that turn raw data into a trusted foundation, driving critical decision-making and operations across the entire system.

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.

Minimum Qualifications

• Masters Degree
• 10+ 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

Preferred Qualifications

• Experience with data versioning tools and frameworks (e.g., DVC, Delta Lake)
• Excellent communication skills and a collaborative mindset
• 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 $184,700 and $324,800, 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. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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Apple accepts applications to this posting on an ongoing basis.