Data Engineer, Operations Finance

Apple • Sunnyvale, CA

1d

About The Position

The Operations Finance team is seeking a motivated Data Engineer to advance its financial data platform. The team works with logistics and supply-chain businesses to understand current and future processes and systems and their effects on finance activities, including costing and forecasting. It also partners with engineering teams to build finance data platforms and automation solutions for logistics.

The role involves understanding, documenting, and re-engineering Apple’s logistics costing and forecasting processes, alongside hands-on work in data querying, dashboard development, and large-scale data analysis. The Data Engineer will design and build scalable data models and modern data and business solutions, including solutions using Dataiku. The role also partners with engineering teams on Agentic and GenAI applications to improve reporting efficiency, data transparency, and strategic decision-making.

Working closely with logistics and supply-chain finance partners and cross-functional engineering teams, the Data Engineer will strengthen data quality, drive automation, and support new capabilities at scale. The position includes making recommendations to senior leadership.

Requirements

• At least 5 years of experience as a data engineer 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.
• Proficiency in Python, including writing clean, maintainable code for data pipelines and automation.
• Experience with scheduling systems and CI/CD tools such as Airflow and Jenkins.
• Hands-on experience with relational database management systems such as Snowflake, PostgreSQL, or similar cloud data warehouses.
• Excellent communication skills.
• Ability to work independently.

Nice To Haves

• Knowledge of Supply Chain, Logistics, Finance, and Accounting processes.

Responsibilities

• Understand and document finance processes in the logistics and supply-chain space.
• Identify and implement process re-engineering and automation opportunities to improve efficiency.
• Collaborate with financial analysts, engineers, and operations experts to understand data needs and translate them into scalable data foundations.
• Build scalable, flexible, high-performance data pipelines optimized for analytics, reporting, and AI/GenAI workloads.
• Apply best practices in data modeling, governance, lineage, quality, and documentation to promote trust and consistency across the data ecosystem.
• Partner with cross-functional engineering teams to build and support vector-ready data models, feature pipelines, metadata systems, and other foundations for Agentic and GenAI applications.
• Make recommendations to senior leadership.

What This Job Offers

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