Sr. Data Engineer - Services Special Projects

Build and run a large-scale real-time data platform that transforms continuous multimodal streams into trusted, governed data for downstream analytics and ML-driven use cases.

Responsibilities

• Design and deliver batch and streaming ETL/ELT pipelines to ingest, process, and model data from diverse sources, including unstructured media and real-time event streams
• Develop and operate Kafka-based ingestion and processing pipelines to support reliable data delivery across services into the data lake
• Create logical and physical data models using dimensional modeling, including versioning and storage pattern optimization (e.g., Parquet, ORC) for ingest, reporting, and operational workloads
• Define and enforce data quality checks, SLAs, and observability standards to keep data accurate, timely, versioned, and trusted
• Enrich raw signals with metadata and attribution to power downstream analytics, billing, planning, and optimization use cases
• Implement data lineage, metadata management, schema governance, versioning, and security aligned with Apple data protection and privacy standards
• Deliver production-ready solutions including logging, anomaly detection, data validation, cleaning, and transformation, with monitoring, debuggability, and continuous improvement
• Partner with ML engineers, data scientists, platform teams, and leadership to translate requirements into scalable, reliable data solutions
• Advance the data stack by contributing to tooling, frameworks, and development/testing/deployment/operations standards

Requirements

• Master’s Degree
• 10+ years of experience in data engineering, including building and maintaining large-scale ETL/ELT pipelines
• Proficiency in data modeling, especially dimensional modeling, and schema design optimized for analytics and reporting
• Experience with databases including SQL/NoSQL (including Postgres, Cassandra, Redis)
• Strong distributed processing experience with Apache Spark
• Strong parallel processing experience including BigTable / Hadoop
• Solid software engineering fundamentals; proven experience with Scala and Java
• Hands-on experience with Apache Kafka, Apache Iceberg, and Apache Flink
• Experience with workflow orchestration tools including Apache Airflow and Beam
• Experience with AWS (examples: 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 with 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 for enrichment and transformation, including LLMs and embedding models
• Hands-on experience deploying, serving, and optimizing LLMs or ML models in 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)

Technologies

• ETL/ELT, Kafka, Parquet, ORC, Dimensional modeling
• DVC, Delta Lake, pgvector, Milvus, FAISS
• Apache Spark, BigTable, Hadoop
• Scala, Java, Apache Iceberg, Apache Flink, Apache Airflow, Beam
• AWS, S3, EMR, Lambda, Glue, Redshift, BigQuery, Kinesis
• Trino, Presto, Snowflake, Docker, Kubernetes, EKS, Jenkins
• Python, PySpark, TigerGraph
• LLMs, embedding models, ONNX Runtime, TensorRT, TensorRT-LLM, Triton, vLLM, TorchServe
• KV-cache, Kafka-based ingestion

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Range of discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
• Eligible for discretionary restricted stock unit awards
• Can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan
• Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation

Pay & benefits

• Base pay range: $184,700 to $324,800 per year
• Apple employees may participate in discretionary employee stock programs, including restricted stock unit awards
• Employees can purchase Apple stock at a discount if they voluntarily participate in the Employee Stock Purchase Plan
• 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

Location: Cupertino, CA (onsite)