Data Platform Engineer for Real-Time ML & Analytics

Apple Inc.; Sunnyvale, Northern (CA, KY); Hybrid; USD 150,000 - 225,000; Full time

Benefits offered by this job

Comprehensive medical and dental

Retirement benefits

Employee stock purchase plan

Relocation assistance

Job summary

Apple Inc. in Sunnyvale, CA seeks a Software Engineer to build next-generation Applied Machine Learning Data Platform (AiDP).

You will design scalable data processing systems, implement real-time and batch pipelines, and develop data tooling across Snowflake, Spark, and Python. You will work with a team handling multi-petabyte scale data with low latency and high concurrency to support fraud prevention and decisioning across Apple platforms.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field.

Responsibilities

• Architect scalable data processing systems for real-time, near-real-time, and batch data pipelines.
• Develop data engineering solutions in Python and advanced SQL.
• Develop self service data engineering applications for business users.
• Design complex Python, PySpark, SQL and data processing for large-scale data platforms including Snowflake and Apache Spark with SparkSQL.
• Developing software system testing and validation procedures and documentation by writing efficient code that results in performant solutions;
• Conferring with data processing or project managers to obtain and refine system requirements.
• Monitoring existing software to correct errors, adapt it to new platform requirements, and implement new functionality.

Skills

Python

SQL

PySpark

Spark

Trino

Flink

Java

Scala

Data warehousing

Data analytics

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

Apache Spark

SparkSQL

Kafka

Flink

Cloud platforms

Job description

Apple Inc. in Sunnyvale, CA seeks a Software Engineer to build next-generation Applied Machine Learning Data Platform (AiDP).

You will design scalable data processing systems, implement real-time and batch pipelines, and develop data tooling across Snowflake, Spark, and Python. You will work with a team handling multi-petabyte scale data with low latency and high concurrency to support fraud prevention and decisioning across Apple platforms.