Product Marketing Customer Analytics Engineer

Apple • Cupertino, CA

1d

About The Position

The Product Marketing Customer Analytics team is seeking an engineer to support customer analytics with advanced, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. Develop and automate large scale, high-performance, scalable platform (batch and/or streaming) to drive faster analytics. Ability to design large-scale, complex applications and frameworks with excellent run-time characteristics such as low-latency, fault-tolerance and availability. Experience in building and maintaining custom frameworks to support engineering/analytics needs. Knowledge of continuous integration, testing methodologies, TDD and agile development methodologies. Partner with analytic consumers and data scientists to build and improve new/existing constructs and solve data engineering problems at scale. Experience in building data pipelines in Spark, Trino, lakehouse or similar distributed platforms & Snowflake. Deploy inclusive data quality checks to ensure high quality of data. Evangelize high quality software engineering practices towards building data infrastructure and pipelines at scale. Structured thinking with ability to easily break down ambiguous problems and propose impactful solutions. Applying Generative AI and Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities.

Requirements

• 3+ years of relevant Engineering experience
• Undergraduate degree in Computer Science, MIS, Engineering, Mathematics or other quantitative discipline required
• 3+ years of experience in data engineering and ETL pipeline development
• 2+ years of experience in Big Data Technologies (Spark,Lakehouse,Trino)
• Knowledge of continuous integration, testing methodologies, TDD and agile development methodologies
• Structured thinking with ability to easily break down ambiguous problems and propose impactful solutions
• Strong documentation and technical writing skills
• Attention to detail and effective verbal/written communication skills

Nice To Haves

• Experience on Kubernetes, Docker preferred
• Familiarity with Retrieval Augmented Generation (RAG) techniques working in conjunction with LLMs
• Experience with creating and consuming Model Context Protocol (MCP) services
• Snowflake knowledge

Responsibilities

• Develop and automate large scale, high-performance, scalable platform (batch and/or streaming) to drive faster analytics
• Design large-scale, complex applications and frameworks with excellent run-time characteristics such as low-latency, fault-tolerance and availability
• Build and maintain custom frameworks to support engineering/analytics needs
• Partner with analytic consumers and data scientists to build and improve new/existing constructs and solve data engineering problems at scale
• Build data pipelines in Spark, Trino, lakehouse or similar distributed platforms & Snowflake
• Deploy inclusive data quality checks to ensure high quality of data
• Evangelize high quality software engineering practices towards building data infrastructure and pipelines at scale
• Apply Generative AI and Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level