US Sales Finance PART Analyst

Apple • Cupertino, CA

6d

About The Position

The US Sales Finance PART (Process, Analytics, Reporting, and Technology) team is looking for a passionate and highly motivated technical Finance Analyst to support Apple's growth, top and bottom line. The PART organization exists to help the Sales Finance team operate at a higher altitude: working across process and systems to reduce manual work, build automated solutions, and unlock insights. Our experience with data foundations and process work positions us well to guide the Sales Finance organization through AI transformation. The PART team builds the library (building organized, curated information assets for Finance) and acts as librarians (subject-matter experts who guide partners to the right answer) for Sales Finance.

This role sits at the intersection of finance, process, and technology. You will spend your time understanding how the US Sales Finance team works today and identifying opportunities to improve the data landscape, eliminate manual deliverables and streamline ad-hoc requests. From there, you will partner with engineering and data teams to deliver enterprise-quality solutions, or build technical solutions yourself. You will be hands-on where it helps: writing SQL to investigate a data question, contributing to our data ecosystem in Dataiku, building a Tableau dashboard or data source to surface important data to humans or systems, drafting requirements that engineering can build against. A solution only counts when it gets used. You will spend time training analysts on what you build, writing documentation, and answering questions across all tools and data, including what you build.

Requirements

• 5+ years of experience in finance-related business analysis, planning, strategy, and/or program and portfolio management roles.
• Bachelor's of Science (BS) or equivalent degree in Finance, Business Management, Computer Science, Engineering or a related field required.
• Comfort with Excel and SQL for ad-hoc analysis.

Nice To Haves

• Strategic & tactical balance - consistent track record of leading cross functional projects, combined with the ability to implement tactical project-level activities.
• User-centered delivery - strong focus on delivering results that work for end-users within technical constraints.
• Business process fluency - ability to quickly learn the end-to-end business processes of a large, multi-function organization.
• Stakeholder communication - ability to clearly and effectively communicate and maintain relationships with a diverse group of internal partners, including representing business problems in terms of product requirements.
• Influence without authority - experience influencing technical teams through credibility and without direct authority.
• Finance background - comfort with financial modeling, accounting principles and scenario analysis.
• Experience working with large datasets in enterprise warehouses (Snowflake, BigQuery, or similar) a plus.
• Data management & governance - understanding of data management best practices to ensure a sustainable and automation-ready data strategy.
• Data accessibility - Tableau or similar; ability to build dashboards or data sources that are usable to the business immediately.
• GenAI tooling - interest and experience with AI based tools to improve process, understand data, create documentation, and drive concrete value.
• AI landscape - strong curiosity about the latest AI developments and thoughtfulness about how to apply them in a governed Finance environment where accuracy is critical.
• Python - scripting for data manipulation, automation, and lightweight tooling (pandas, Streamlit).
• Workflow automation - Dataiku or similar low-code platforms, ability to convert manual Excel processes into repeatable pipelines.

Responsibilities

• Understand how the US Sales Finance team works today.
• Identify opportunities to improve the data landscape.
• Eliminate manual deliverables.
• Streamline ad-hoc requests.
• Partner with engineering and data teams to deliver enterprise-quality solutions.
• Build technical solutions.
• Write SQL to investigate data questions.
• Contribute to the data ecosystem in Dataiku.
• Build Tableau dashboards or data sources.
• Draft requirements for engineering.
• Train analysts on built solutions.
• Write documentation.
• Answer questions across all tools and data.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree