Imagine what you could do here. At Apple, we don’t just create products – we create experiences that revolutionize industries. The diversity of our people and ideas fuels the innovation that runs through everything we do. Bring your passion for data and technology to your work and you could have an incredible impact!
The Workflow Solutions team, within the Process, Analytics, Reporting & Technology (PART) Data Operations group, is seeking a talented and highly motivated Data Engineer. We empower Apple’s Finance teams to operate more efficiently and make data-driven decisions by building and deploying innovative, user-friendly data applications. You will directly improve the day-to-day workflows of financial analysts, helping them unlock insights and drive business impact. This is a hands-on role where you’ll see your work used by key stakeholders across the organization.We are looking for a strong Data Engineer with a passion for building intuitive web applications that solve real-world business problems. This role is at the intersection of data engineering, software development, and financial process optimization. You will be responsible for designing, building, and deploying lightweight web interfaces and data tools – primarily using Python frameworks like Streamlit – to streamline financial analysis, reporting, and decision-making. Success in this role requires an individual who can quickly understand complex financial processes, translate those processes into technical specifications, and deliver high-quality, user-friendly data applications. You’ll be a key collaborator with financial analysts, data scientists, and other engineers, building trust through clear communication and impactful solutions. Responsibilities: - Collaborate with financial analysts to deeply understand their current workflows, pain points, and analytical needs. - Design, develop, and deploy lightweight web applications (using Python frameworks like Streamlit) to automate tasks, visualize data, and improve the efficiency of financial processes. - Write clean, well-documented, and maintainable Python code. - Connect applications to various data sources (databases, APIs, data lakes) within Apple’s data ecosystem. - Implement robust error handling, logging, and monitoring for applications. - Manage the full application lifecycle, from development and testing to deployment and maintenance. - Gather user feedback and iterate on applications to continuously improve their usability and functionality. - Work with data scientists to integrate analytical models and algorithms into data applications. - Contribute to the development of best practices for data application development and deployment within the team. - Document applications, data flows, and technical specifications.