P2P Data & Automation Analyst

GAQ327R181

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.

Databricks is executing a multi-year Procure-to-Pay transformation spanning an expense management platform migration, the BrickBuy enterprise procurement portal, a managed services onboarding, and policy and process redesign initiatives. This role sits embedded within Procurement — not in a central IT or analytics function — and operates in accordance with the Finance Data Strategy governance framework to drive rapid P2P process transformation by designing, deploying, and scaling automation and data solutions directly within business workflows.

This is a builder role for someone who wants to own outcomes, not tickets: the person will sit inside the processes they are automating, ship working solutions in weeks rather than quarters, and carry them through adoption — pairing hands-on technical delivery with the change management discipline needed to make new ways of working stick.

The impact you will have:

• Business process ownership. Own designated P2P sub-processes end to end — intake-to-PO, invoice exception handling, supplier onboarding, expense workflows — including process mapping, baseline metrics (cycle time, touch rates, exception volumes), and redesign. Act as the recognized process owner who is accountable for how the process performs, not just how it is documented.
• Requirements & solution design. Translate pain points raised by requesters, approvers, buyers, and AP into structured requirements and solution designs. Work within the Finance Data Strategy governance framework for data definitions, source-of-truth alignment, access controls, and quality standards — solutions must tie to certified Finance data, not shadow datasets.
• Embedded automation. Design, deploy, and scale automations directly within business workflows and the systems where work actually happens (ZIP, SAP, NetSuite, expense platform, BrickBuy) — including AI/LLM-assisted triage, auto-routing, data enrichment, exception auto-resolution, and notification/nudge logic. Build in production-adjacent environments with appropriate guardrails rather than standalone tools users must remember to visit.
• Rapid iteration. Operate on a ship-measure-iterate cadence: release minimum viable automations in weeks, instrument them from day one, and refine based on usage data and user feedback. Maintain sandbox-to-production discipline consistent with Finance Data Strategy and SOX/control requirements.
• Data & measurement. Build and maintain the P2P datasets, dashboards, and metrics that the transformation runs on — cycle time, Fast P