Summary

Apple is a place where extraordinary people gather to do their best work. Together we create products and experiences people once couldn’t have imagined - and now can’t imagine living without. If you’re motivated by the idea of making a real impact, and joining a team where we pride ourselves in being one of the most diverse and inclusive companies in the world, a career with Apple might be your dream job!

You will become a member of the Sales Finance team at Apple. With approximately 150 employees based across 4 regional hubs within EMEIA (Europe, Middle East, India and Africa), we create value, collaborating with many teams to provide outstanding commercial and financial support. We set the bar high; go out of our way to help others; share knowledge; filter out noise to focus on the essential; encourage the very best from ourselves and the team; and drive the right course of action. To do all of this you will be an excellent communicator, collaborator and innovator, with a passion for debate and inclusion.

Description

This role resides within the Process, Analytics, Reporting and Technology (PART) Enablement Team. We empower Apple’s EMEIA Sales 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 organisation.

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 optimisation. 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. You will also build data pipelines to support business needs.

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. Ideal candidates also have a strong understanding of UI/UX principles for designing intuitive, self-service data applications that drive user adoption across business teams with varying levels of technical expertise.

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, visualise 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.
• Build data pipelines to support business needs and financial analyst reporting and insights.
• Automate current workstreams with efficiencies and maintenance built into the process.
• Document applications, data flows, and technical specifications.
  
  

Minimum Qualifications

• 5+ years of experience in data engineering or software development with a focus on building data applications.
• Strong proficiency in Python programming and experience with web frameworks (required: Streamlit, preferred: Flask, Django).
• Experience working with relational databases (e.g., SQL Server, PostgreSQL) and data lakes.
• Familiarity with data visualisation techniques and tools (e.g., Matplotlib, Seaborn, Plotly).
• Experience with version control systems (e.g., Git).
• Experience in modern data warehouses (e.g., Snowflake and Dremio) and ETL processes using modern orchestration tools (e.g. Airflow, Metaflow).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
• Experience working with large-scale, complex financial or commercial datasets.
• Experience implementing data quality frameworks, monitoring solutions, and governance controls.
• Exposure to Dataiku or similar data science platforms.
• Experience working closely with analytics, BI, or data science teams to support downstream use cases.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
• Ability to communicate complex technical concepts clearly to non-technical stakeholders.
• Detail-oriented and self-motivated individual able to function effectively when working independently or in a team.
• Bachelor’s degree in Computer Science, Data Science, or a related field required.
  
  

Preferred Qualifications

• Familiarity with UI/UX best practices, user-centred design, and data visualisation principles.
• Experience using Tableau or SAP BusinessObjects.
• Financial systems and/or Sales Finance domain experience is a plus.
  
  

At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more