EMEIA Sales Finance Analytics Engineer

Apple is a place where extraordinary people gather to do their best work. Together we create products and experiences people once couldnt have imagined - and now cant imagine living without. If youre 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!nYou 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.

nThis role resides within the Process Analytics Reporting and Technology (PART) Enablement Team. We empower Apples 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 youll see your work used by key stakeholders across the organisation. nWe 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 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. Youll 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.

Collaborate with financial analysts to deeply understand their current workflows pain points and analytical develop and deploy lightweight web applications (using Python frameworks like Streamlit) to automate tasks visualise data and improve the efficiency of financial clean well-documented and maintainable Python applications to various data sources (databases APIs data lakes) within Apples data robust error handling logging and monitoring for the full application lifecycle from development and testing to deployment and user feedback and iterate on applications to continuously improve their usability and with data scientists to integrate analytical models and algorithms into data to the development of best practices for data application development and deployment within the data pipelines to support business needs and financial analyst reporting and insights. nAutomate current workstreams with efficiencies and maintenance built into the applications data flows and technical specifications.

n5 years of experience in data engineering or software development with a focus on building data proficiency in Python programming and experience with web frameworks (required: Streamlitpreferred: Flask Django).nExperience working with relational databases (e.g. SQL Server PostgreSQL) and data with data visualisation techniques and tools (e.g. Matplotlib Seaborn Plotly).nExperience with version control systems (e.g. Git).nExperience in modern data warehouses (e.g. Snowflake and Dremio) and ETL processes using modern orchestration tools (e.g. Airflow Metaflow).nExperience with cloud platforms (e.g. AWS Azure GCP) is a working with large-scale complex financial or commercial implementing data quality frameworks monitoring solutions and governance to Dataiku or similar data science working closely with analytics BI or data science teams to support downstream use problem-solving skills and attention to communication and collaboration to communicate complex technical concepts clearly to non-technical -oriented and self-motivated individual able to function effectively when working independently or in a degree in Computer Science Data Science or a related field required.

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