Design and maintain large-scale ETL/ELT data pipelines and analytics-focused data models.
Build and operate distributed data processing systems using Spark, Hadoop, and related technologies.
Work with SQL/NoSQL databases (Postgres, Cassandra, Redis) and data lake architectures.
Implement data governance, security, and privacy controls in line with regulations.
Deploy and optimize ML inference in production pipelines (LLMs, embeddings, ONNX/TensorRT, Triton or similar).

Key requirements

Design and maintain large-scale ETL/ELT data pipelines and analytics-focused data models.
Build and operate distributed data processing systems using Spark, Hadoop, and related technologies.
Work with SQL/NoSQL databases (Postgres, Cassandra, Redis) and data lake architectures.
Implement data governance, security, and privacy controls in line with regulations.
Deploy and optimize ML inference in production pipelines (LLMs, embeddings, ONNX/TensorRT, Triton or similar).

Jobs at Apple

71 active roles from this employer in the JobMatcher catalog.

All company jobs

Jobs at Apple

71 active roles from this employer in the JobMatcher catalog.

All company jobs

About the role

Apple is seeking a Senior Data Engineer for a Services Special Project based in Cupertino, California. This on-site role is responsible for designing, building, and operating massively scalable ETL/ELT pipelines, data architecture, and applied ML pipelines to transform raw data into a trusted foundation for real-time analytics and decision making across the platform. You will enrich data with language embeddings and model inference as needed to support downstream applications.

Responsibilities

Qualifications:

Design and maintain large-scale ETL/ELT data pipelines and analytics-focused data models.
Build and operate distributed data processing systems using Spark, Hadoop, and related technologies.
Work with SQL/NoSQL databases (Postgres, Cassandra, Redis) and data lake architectures.
Implement data governance, security, and privacy controls in line with regulations.
Deploy and optimize ML inference in production pipelines (LLMs, embeddings, ONNX/TensorRT, Triton or similar).
Collaborate across teams to enable real-time analytics for downstream applications.
Masters degree with 10+ years of data engineering experience.
Deep expertise in data modeling (dimensional models) and scalable pipelines.
Proficiency with Python, PySpark, Scala/Java; hands-on with Kafka, Iceberg, Flink; Airflow/Beam; AWS services (S3, EMR, Lambda, Glue, Redshift, BigQuery, Kinesis) or equivalent.
Experience with Big Data ecosystems (Spark, Hadoop), containerization (Docker, Kubernetes/EKS), and CI/CD (Jenkins).
Familiarity with data governance, security, and privacy practices.
-

About the role

Apple is seeking a Senior Data Engineer for a Services Special Project based in Cupertino, California. This on-site role is responsible for designing, building, and operating massively scalable ETL/ELT pipelines, data architecture, and applied ML pipelines to transform raw data into a trusted foundation for real-time analytics and decision making across the platform. You will enrich data with language embeddings and model inference as needed to support downstream applications.

Responsibilities

Qualifications:

Design and maintain large-scale ETL/ELT data pipelines and analytics-focused data models.
Build and operate distributed data processing systems using Spark, Hadoop, and related technologies.
Work with SQL/NoSQL databases (Postgres, Cassandra, Redis) and data lake architectures.
Implement data governance, security, and privacy controls in line with regulations.
Deploy and optimize ML inference in production pipelines (LLMs, embeddings, ONNX/TensorRT, Triton or similar).
Collaborate across teams to enable real-time analytics for downstream applications.
Masters degree with 10+ years of data engineering experience.
Deep expertise in data modeling (dimensional models) and scalable pipelines.
Proficiency with Python, PySpark, Scala/Java; hands-on with Kafka, Iceberg, Flink; Airflow/Beam; AWS services (S3, EMR, Lambda, Glue, Redshift, BigQuery, Kinesis) or equivalent.
Experience with Big Data ecosystems (Spark, Hadoop), containerization (Docker, Kubernetes/EKS), and CI/CD (Jenkins).
Familiarity with data governance, security, and privacy practices.
-

Track similar jobs

Get email alerts when new roles like this are posted.

Based on: Senior Data Engineer