Finance Data Engineer

Summary

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Product Marketing Customer Analytics team is seeking a data 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.

Description

• 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 @ 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
• Communication Strong documentation and technical writing skills.
• Attention to detail and effective verbal/written communication skills.

  Minimum Qualifications

  • 5+ years of relevant Data Engineering experience
  • Undergraduate degree in Computer Science, MIS, Engineering, Mathematics or other quantitative discipline required.

  Preferred Qualifications

  • 5+ years of experience in data engineering and ETL pipeline development
  • 5+ years of experience in Big Data Technologies (Spark,Lakehouse,Trino)
  • 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
  • Experience with Snowflake

  Pay & Benefits

  At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $149,200 and $249,000, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant