Finance Data Engineer

Apple; Austin (TX); Presencial; USD 149.000 - 249.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical and dental coverage

Retirement benefits

Employee stock programs

Tuition reimbursement

Relocation assistance

Discretionary bonuses

Descripción de la vacante

Apple in Austin, TX seeks a Finance Data Engineer to design and operate scalable customer analytics data pipelines and platforms, enabling analytics, data analysis, and data science teams. You will build batch and streaming data infrastructure, implement data quality checks, and collaborate with analytics consumers and data scientists to solve data engineering problems at scale.

The role emphasizes strong documentation, effective communication, and applying Generative AI and RAG techniques to

Formación

• 5+ years of relevant Data Engineering experience.
• 5+ years of experience in ETL pipeline development.
• 5+ years of experience in Big Data Technologies including Spark, Lakehouse, and Trino.

Responsabilidades

• Develop and automate large-scale, high-performance data platforms for batch and/or streaming to improve analytics velocity.
• Design scalable applications with low latency, fault-tolerance, and high availability.
• Build and maintain data pipelines using Spark, Trino, lakehouse, and Snowflake.
• Collaborate with analytics consumers and data scientists to improve data constructs at scale.
• Implement inclusive data quality checks to ensure high-quality data for downstream use.
• Promote best-practice software engineering for data infrastructure and pipelines.

Conocimientos

Finance data engineering

Batch & streaming pipelines

Data quality practices

Collaboration with analytics teams

Educación

Undergraduate degree in Computer Science, MIS, Engineering, Mathematics

Herramientas

Spark

Trino

Lakehouse

Snowflake

Kubernetes

Docker

MCP

LLMs

RAG

Descripción del empleo

The Product Marketing Customer Analytics team is seeking a Finance Data Engineer to design and operate advanced, scalable customer analytics data pipelines and platforms. The role supports analytics, data analysis, and data science through batch and streaming infrastructure, data quality practices, and close collaboration with analytics consumers and data scientists.

Location

Austin, TX (onsite)

Salary

USD 149,200 - 249,000 per year

Responsibilities

• Develop and automate large-scale, high-performance, scalable data platforms for batch and/or streaming to improve analytics velocity.
• Design large-scale, complex applications and frameworks with strong runtime characteristics such as low latency, fault tolerance, and availability.
• Build and maintain custom frameworks that support engineering and analytics needs.
• Partner with analytics consumers and data scientists to improve existing constructs and solve data engineering problems at scale.
• Build and maintain data pipelines using Spark, Trino, lakehouse, and/or similar distributed platforms, including Snowflake.
• Implement inclusive data quality checks to help ensure high-quality data for downstream use.
• Promote high-quality software engineering practices for data infrastructure and pipelines built at scale.
• Use structured thinking to break down ambiguous problems and propose impactful solutions.
• Apply Generative AI and Retrieval Augmented Generation (RAG) techniques to enhance data analytics capabilities.
• Maintain strong documentation and technical writing, with effective verbal and written communication skills.

Required Qualifications

• 5+ years of relevant Data Engineering experience.
• Undergraduate degree in Computer Science, MIS, Engineering, Mathematics, or another quantitative discipline (required).
• 5+ years of experience in data engineering and ETL pipeline development.
• 5+ years of experience in Big Data Technologies including Spark, Lakehouse, and Trino.

Preferred Qualifications

• Experience with Kubernetes and Docker (preferred).
• Familiarity with RAG techniques in conjunction with LLMs.
• Experience creating and consuming Model Context Protocol (MCP) services.
• Experience with Snowflake.

Technologies

• Spark
• Trino
• Lakehouse
• Snowflake
• Kubernetes
• Docker
• Generative AI
• Retrieval Augmented Generation (RAG)
• LLMs
• Model Context Protocol (MCP)

Benefits

• Comprehensive medical and dental coverage.
• Retirement benefits.
• Discounted products and free services.
• Reimbursement for certain educational expenses, including tuition.
• Opportunity to become an Apple shareholder through Apple’s discretionary employee stock programs.
• Eligible for discretionary restricted stock unit awards.
• Ability to purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan.
• Discretionary bonuses or commission payments, and relocation if eligible.
• Base pay range between $149,200 and $249,000.