Senior Data Engineer – Real-Time ETL & ML Pipelines

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

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Educational reimbursement

Tuition support

Employee stock programs

Relocation assistance

Discretionary bonuses

Job summary

Apple seeks an experienced Data Engineer to design, build, and operate massively scalable ETL/ELT pipelines that turn raw data into a trusted foundation for analytics and ML. You will own data modeling, governance, and streaming/batch processing across diverse data sources.

Collaborate with ML engineers and platform teams to scale data solutions, improve data quality, and support critical decision-making across the data lake ecosystem for billions of Apple customers.

Qualifications

• Ten or more years in data engineering with large-scale ETL/ELT pipelines.
• Strong data modeling, especially analytics-oriented schemas.
• Experience with SQL/NoSQL databases and distributed processing.

Responsibilities

• Build batch and streaming ETL/ELT pipelines from diverse sources.
• Develop Kafka-based ingestion and processing pipelines for a data lake.
• Create robust data models, governance, and quality checks.
• Collaborate with ML engineers and platform teams to scale data solutions.
• Deliver monitoring, logging, and observability for data pipelines.

Skills

ETL/ELT design

Data modeling

Apache Spark

Kafka

Airflow/Beam

Python

PySpark

SQL/NoSQL

LLM embeddings

Docker/Kubernetes

Education

Masters Degree

Tools

Iceberg

Flink

Jenkins

Airflow

Kubernetes

Docker

BigQuery

Redshift

S3

Kinesis

Job description

Apple seeks an experienced Data Engineer to design, build, and operate massively scalable ETL/ELT pipelines that turn raw data into a trusted foundation for analytics and ML. You will own data modeling, governance, and streaming/batch processing across diverse data sources.

Collaborate with ML engineers and platform teams to scale data solutions, improve data quality, and support critical decision-making across the data lake ecosystem for billions of Apple customers.