Job Description
This Finance Business Partner role sits inside Amazon Now’s MEATR (Middle East, Africa, Turkey & Russia) finance function, supporting the team that runs Amazon’s fast-delivery commerce business. The role is built around partnership rather than pure reporting: the person works alongside senior business leaders to shape decisions, not just record their outcomes after the fact.
Expect the day-to-day to involve building and maintaining financial models for the Amazon Now business, analyzing performance against targets, flagging variances early, and presenting findings in a way that non-finance stakeholders can act on. Because Amazon Now is an operationally intense, fast-moving part of the business, the numbers move quickly, and the finance partner needs to keep pace with that rhythm rather than working purely on a monthly reporting cycle.
A meaningful part of the role is stakeholder management: working with operations, logistics and commercial leaders who think in terms of delivery speed and customer experience, and helping them see the financial consequences of operational choices clearly. That means the finance partner needs to be comfortable challenging assumptions respectfully and building credibility with people who are not finance specialists themselves.
It suits someone with a strong analytical finance background — FP&A, commercial finance, or business partnering — who wants exposure to a high-growth, operationally complex part of Amazon’s business, with real influence over how a regional leadership team makes decisions.
Impact of the Job
A Finance Business Partner on Amazon Now directly shapes how a fast-growing, operationally complex business manages its economics. Rapid delivery businesses have thin margins and many moving cost levers — fulfillment, last-mile delivery, inventory positioning — and poor financial visibility can mean problems go unnoticed until they are expensive to fix. By catching variances early and building models that leadership actually trusts, this role gives the business the ability to course-correct quickly rather than reactively. Good business partnering also changes behavior upstream: when operational leaders understand the financial consequences of their decisions clearly, they tend to make better ones without finance having to intervene after the fact. Over time, that compounds into a business that scales more efficiently. For a regional leadership team managing a business this fast-moving, having a finance partner who can translate operational reality into financial clarity is one of the clearest levers available for protecting margin while the business keeps growing.
Job Seeker Benefit
This role gives a finance professional direct exposure to one of the most operationally demanding parts of Amazon's business, which is a different skill set from traditional corporate FP&A. Fast-delivery commerce involves a constant interplay between logistics, inventory, customer experience and cost, and learning to model and influence that environment builds a genuinely commercial, operationally literate finance skill set rather than a purely reporting-focused one. Sitting inside Amazon also means exposure to some of the most sophisticated financial planning tools, forecasting rigor and data infrastructure in the industry, which is valuable experience to carry into future roles anywhere. Because the position is explicitly a business partnering role rather than a back-office finance job, it also builds influencing and stakeholder management skills that are hard to develop in roles with less senior exposure — presenting to and challenging operational leadership regularly is excellent preparation for more senior finance leadership roles. For someone early-to-mid career in finance, this kind of seat is a strong platform toward regional finance manager, FP&A lead, or business unit CFO-track roles, both within Amazon and in other high-growth commerce or logistics businesses afterward. Beyond the immediate scope of the role, it also offers genuine exposure to how a large, well-run organization actually operates internally, which is knowledge that's hard to gain any other way and tends to be valued by future employers regardless of the specific next role someone takes.
Suggested Resume Keywords
Consider including these terms in your resume for this role:
Requirements
- Several years of experience in financial planning & analysis, commercial finance, or business partnering
- Strong financial modeling skills and comfort working with large, messy operational datasets
- Experience presenting financial analysis to senior non-finance stakeholders
- Track record of partnering with operations or commercial teams rather than working in isolation
- Advanced Excel/spreadsheet modeling skills; experience with BI or data tools is an advantage
- Ability to work at pace in a fast-moving, operationally intensive business environment
- Strong communication skills, including the ability to influence and challenge constructively
Interview Questions to Prepare For
Tell me about a time your financial analysis changed an operational decision.
Look for concrete influence on outcomes, not just producing a report that was ignored.
How do you build a financial model for a business where the underlying operations change quickly?
Assess flexibility in modeling approach and awareness of data quality issues.
Describe a situation where you had to challenge a senior stakeholder's assumption.
Look for tact combined with willingness to push back using data.
How do you prioritize when multiple variance issues surface at the same time?
Check for a clear framework for materiality and urgency, not just gut feel.
What's your experience partnering with operations or logistics teams specifically?
Confirm genuine exposure to operational finance, not purely corporate reporting.
Walk me through how you would explain a margin decline to a non-finance operations leader.
Look for clarity, simplification, and framing around actionable levers.
Tell me about the messiest dataset you've had to model from, and how you handled it.
Assess practical problem-solving and comfort with real-world data imperfection.