Jobs / United States / Databricks
P2P Data & Automation Lead
Databricks · 🇺🇸 San Francisco, California
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 445 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 78 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Databricks paid sponsored hires in similar roles8 certified filings for “Data Scientist” (Statisticians) in CA: $153k–$195k, median $153k. Most were filed at wage level II (75%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Databricks
The US Department of Labor certified 445 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 78 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Databricks →
About the role
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 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 engageme