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Apple

Data Engineer, Operations Finance

Apple Sunnyvale, California, United States

Computers and Electronics Manufacturing · 10,001+ employees

Oct 20
data-engineer Senior (5-10 yrs) Full-time United States
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About the role

The Data Engineer will design and build scalable data models and automation solutions to support logistics and supply chain finance operations. They will collaborate with cross-functional engineering teams to develop GenAI applications and improve financial reporting efficiency.

What they look for

Data Engineering SQL Python Data Modeling Dashboard Development Data Analysis Dataiku GenAI Automation Supply Chain Logistics Finance Snowflake PostgreSQL Cloud Data Warehouses CI/CD

Requirements

Candidates must have at least 5 years of experience in data engineering and a bachelor's degree in Computer Science or a related field. Proficiency in advanced SQL and Python is required, along with strong analytical and communication skills.

Full description

The Operations Finance team is looking for a passionate and highly motivated Data Engineer to drive our financial data platform forward. We work with logistics and supply-chain business to understand current and future processes and systems, and its impact on finance activities including costing and forecasting. We also work with engineering teams to build finance data platforms and automation solutions to support logistics business. If you thrive in a fast-moving, collaborative environment and want to solve complex problems with new technology-driven data systems, we’d love to hear from you.

Description

Operations Finance Data Engineer role requires you understand, document and re-engineer Apple's logistics costing and forecast processes, while bringing strong technical expertise in data querying, dashboard development, and large-scale data analysis. You’ll design and build scalable data models, modern Data & Business solutions leveraging tools such as Dataiku, partner with engineering teams to create Agentic/GenAI applications to improve reporting efficiency, enhance data transparency, and support strategic decision-making. This is a hands-on role working closely with logistics & supply chain finance business partners and cross-functional engineering teams, while also making recommendations to senior leadership. Your work will strengthen data quality, drive automation, and unlock new capabilities at scale.

Minimum Qualifications

Minimum of 5 years of working 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 Python proficiency, comfortable writing clean, maintainable Python for data pipelines and automation

Preferred Qualifications

Experience with scheduling systems and CI/CD tools such as Airflow, Jenkins, etc. Hands-on experience working with relational database management system such as Snowflake, PostgreSQL or similar cloud data warehouses Supply Chain, Logistics, Finance and Accounting process knowledge is a plus Excellent communication skills and ability to work independently

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