Jobs / United States / Databricks
Partner Engineer: Partner Intelligence, AI & Apps
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 roles103 certified filings for “Software Engineer” (Software Developers) in CA: $158k–$191k, median $188k. Most were filed at wage level II (47%) — 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
RDQ427R535 At Databricks , we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role This partner intelligence engineer owns the internal tooling that runs the ISV partner organization: the pipelines, dashboards, Genie spaces, metric views, and the AI applications and workflows we use to operate the partner business. You will build and maintain that stack on Databricks and use the platform heavily, every day. You will also work with the Apps and AI teams as an early user of new features, and with Developer Relations to share what you build. The role is based in San Francisco and reports into Partner Engineering. Impact you will have • Data pipelines and quality: Build, schedule, and maintain the data pipelines that run the partner business, and own their quality, monitoring, and governance. • Partner metrics and measurement: Own how we measure partners: the metrics, metric views, and definitions that serve as the source of truth for partner performance and health. • Reporting and self-serve analytics: Build and maintain the dashboards, Genie spaces, and apps the team uses to run the business day to day. • Internal AI apps: Build AI applications and agentic workflows that automate how we run the partner business. • Partner AI platforms: Build real internal tools on partner products like Replit, Lovable, Cursor, Claude, and Codex, and bring what you learn about their strengths and gaps back to the AI and Apps partnerships. • Early Databricks adopter and DevRel: Try new Databricks features early (Apps, Genie, metric views, AI/BI, Lakebase, Agent Bricks), give product teams direct feedback, and work with Developer Relations to turn what you build into reusable examples. Required Qualifications • 3+ years in data engineering, analytics engineering, or a similar hands-on data or AI role. • Heavy hands-on production experience with Databricks data engineering and analytics tool • Strong SQL and Python, with experience building and maintaining production data pipelines. • Experience building the analytics layer a team runs on: dashboards, semantic or metric layers, and clear metric definitions. • Experience building AI applications or agentic workflows (LLM-powered apps and automations). • Regular hands-on use of AI code-gen and app-building tools (Replit, Lovable, Cursor, Claude, Codex). You use them in your day-to-day work. • Clear communicator who works well in fast-moving, sometimes ambiguous situations. • Strong propensity for GSD → Gets Stuff Done! Preferred • Depth in Databricks analytics and AI features: Genie, AI/BI, metric views, Lakebase, Agent Bricks. • dbt or a similar transformation framework, and modern analytics-engineering practices. • Experience defining business metrics and KPI frameworks. • Open-source contributions or community work in data and AI. Pay Range Transparency 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 limi