Data Engineer, Operations Finance
Data Engineer on Apple's Operations Finance team, building the financial data platform behind logistics costing and forecasting. Day-to-day: SQL/Python data pipelines, scalable data models, dashboards with tools like Dataiku, and partnering with engineering on GenAI/Agentic reporting automation.
- Compensation
- Not disclosed
- Location
- Sunnyvale
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Minimum 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
- Python proficiency for data pipelines and automation
Nice to have
- Experience with scheduling systems and CI/CD tools such as Airflow, Jenkins
- Hands-on experience with RDBMS such as Snowflake, PostgreSQL or similar cloud data warehouses
- Supply Chain, Logistics, Finance and Accounting process knowledge
- Excellent communication skills and ability to work independently
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.
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