P2P Data & Automation Lead

P2P Data & Automation Lead

San Francisco, California

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.

• 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 Pass performance, first‑pass yield, policy compliance, automation coverage, and adoption rates — and report against them in existing operating rhythms (e.g., quarterly business reviews), with numbers that tie across reports and to source data.
• User adoption & change management. Own the adoption of what you build. Design role‑based training and enablement for affected requesters, approvers, and P2P operations staff; produce launch communications, FAQ/help content, and go‑live announcements in a style consistent with executive reporting norms (concise, structured, blockers called out explicitly); run feedback loops with change champions across subsidiaries; and actively identify and mitigate resistance rather than assuming usage will follow deployment.
• Day‑to‑day prioritization. Run the intake and backlog for automation and data requests across Procurement: triage incoming asks, prioritize by value, effort, and risk, publish a visible roadmap, and make defensible trade‑off calls daily — protecting capacity for transformation priorities while handling operational requests.
• Stakeholder engagement. Partner closely with Procurement operations, the Finance Data team, the CIO org, and managed services partners; represent Procurement in Finance Data Strategy governance forums; and ensure automation work lands coherently alongside parallel workstreams (expense platform migration, BrickBuy rollout, Global Procurement Policy adoption, managed services transition).

• 4–8 years in data analytics, process automation, or operations roles within P2P, procurement, or finance — with demonstrable examples of automations or data products you built, shipped, and scaled yourself.
• Hands‑on technical skills: SQL and Python (or equivalent), workflow and integration tooling (iPaaS, RPA, or native platform automation), and dashboarding/BI. Experience building on the Databricks platform and applying LLM/AI tooling to business workflows is a strong plus.
• Working knowledge of P2P systems and data — ERP (SAP or NetSuite), procurement intake/orchestration platforms (ZIP or similar), and expense management tools — including how transactions, approvals, and master data flow between them.
• Experience operating within a data governance framework: certified data sources, data quality standards, access controls, and audit/SOX considerations — comfortable moving fast without going around governance.
• Change management fluency: track record of driving adoption of new tools or processes through training, communications, champion networks, and adoption metrics — not just deploying and moving on.
• Strong prioritization judgment and stakeholder management: able to run a busy intake, say no with a rationale, and communicate crisply to audiences from frontline requesters to executives.
• Experience in a high‑growth, multi‑entity organization (multiple subsidiaries/geographies) is a plus; formal change management certification (Prosci, ADKAR, or equivalent) or process improvement certification (Lean/Six Sigma) preferred but not required.

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .

Zone 1 Pay Range $186,000 — $255,750 USD

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .

Zone 2 Pay Range $167,400 — $230,250 USD

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .

Zone 3 Pay Range $158,100 — $217,350 USD

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non‑commissionable roles or on‑target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job‑related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .

Zone 4 Pay Range $148,800 — $204,600 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .

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