Finance Data Engineer — Scalable Spark Pipelines & AI Insights

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

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