P2P Automation Lead & Data Engineer

Databricks; California (MO); On-site; USD 180,000 - 256,000; Full time

Job summary

Databricks is seeking a procurement automation professional embedded in Procurement to own end-to-end P2P process redesign and automation within business workflows. You will ship working solutions in weeks, measure outcomes, and drive adoption with change management across subsidiaries.

Key tasks include translating pain points into requirements, building automation (AI-assisted triage, routing, data enrichment), and ensuring governance and data quality align with Finance Data Strategy.

Qualifications

• 4–8 years in data analytics, process automation, or operations roles within P2P, procurement, or finance — with demonstrable automations you built and deployed.
• Hands-on SQL and Python; workflow/integration tooling; dashboarding/BI; experience on Databricks; AI tooling is a strong plus.
• Experience with ERP systems (SAP/NetSuite) and procurement platforms; data governance, data quality, and SOX considerations.
• Change-management readiness: training, communications, adoption metrics, and cross-stakeholder collaboration.

Responsibilities

• Own designated P2P sub-processes end-to-end (intake-to-PO, invoices, onboarding) with process mapping and metrics.
• Translate requester pain points into structured requirements and solution designs within the Finance Data Strategy framework.
• Design, deploy, and scale automation inside business workflows (ZIP, SAP, NetSuite, expense platforms) including AI-assisted triage and auto-routing.
• Ship minimum viable automations in weeks; measure usage and refine based on feedback and data.

Skills

SQL

Python

Workflow automation

BI dashboards

Databricks platform

LLM/AI tooling

Tools

SAP

NetSuite

ZIP

iPaaS

RPA

Job description

Databricks is seeking a procurement automation professional embedded in Procurement to own end-to-end P2P process redesign and automation within business workflows. You will ship working solutions in weeks, measure outcomes, and drive adoption with change management across subsidiaries.

Key tasks include translating pain points into requirements, building automation (AI-assisted triage, routing, data enrichment), and ensuring governance and data quality align with Finance Data Strategy.