Data Engineer, Operations Finance

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 Apples 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.Understand and document finance processes in the logistics & supply chain space. Identify and implement process reengineering and automation opportunities to drive efficiency gains. Collaborate with financial analysts, engineers, and operations experts to understand data needs and translate them into scalable data foundational structures. Build scalable, flexible, and high-performance data pipelines optimized for analytics, reporting, and AI/GenAI workloads. Implement best practices in data modeling, governance, lineage, quality, and documentation to drive 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 required for Agentic & GenAI applications.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 automationExperience 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