Data Engineer, Finance & Operations Analytics (GenAI-ready)

Apple, Inc.; Sunnyvale (CA); Presencial; USD 149.000 - 249.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Comprehensive medical and dental cover

Retirement benefits

Employee stock programs

Tuition reimbursement

Descripción de la vacante

Apple, Inc. in Sunnyvale, CA is hiring a data engineer to drive our logistics costing and forecasting data platform.

You will design scalable data models, build data pipelines, and partner with engineering teams to enable analytics, reporting, and GenAI-driven solutions. You will work closely with logistics and supply chain finance partners to improve data quality, automation, and transparency for strategic decision-making.

Formación

• Minimum 5 years building end-to-end data pipelines.
• Bachelor’s degree in Computer Science, Information Systems, or equivalent.
• Advanced SQL skills for complex transformations, optimization, and troubleshooting.
• Python proficiency for data pipelines and automation.

Responsabilidades

• Understand and document finance processes in logistics and supply chain.
• Identify and implement automation opportunities to drive efficiency.
• Collaborate with analysts, engineers, and operations experts to translate data needs into scalable structures.
• Build scalable, high-performance data pipelines for analytics, reporting, and AI workloads.
• Implement data modeling, governance, lineage, and quality best practices.
• Partner with cross-functional teams to support GenAI applications and data foundations.

Conocimientos

Data engineering

Advanced SQL

Python

Educación

Bachelor's degree in CS/IS

Herramientas

Airflow

Jenkins

Snowflake

PostgreSQL

Descripción del empleo

Apple, Inc. in Sunnyvale, CA is hiring a data engineer to drive our logistics costing and forecasting data platform.

You will design scalable data models, build data pipelines, and partner with engineering teams to enable analytics, reporting, and GenAI-driven solutions. You will work closely with logistics and supply chain finance partners to improve data quality, automation, and transparency for strategic decision-making.