Jobs / United States / Databricks
Lead Technical Enablement Specialist, Field Capability & Readiness
Databricks · 🇺🇸 United States
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 roles1 certified filing for “Sr. Enablement Program Specialist” (Management Analysts) in CA: $172k–$172k, median $172k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% 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.
Or apply yourself on the official page →
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
SLSQ227R703 About the Role The Field Engineering role is changing quickly. AI is changing how technical work gets done, products and customer needs are evolving faster, and the capabilities that distinguish an exceptional FE today will not be exactly the same ones that matter tomorrow. Databricks is looking for a Lead Technical Enablement Specialist to help define and build the capability engine for our global Field Engineering organization. You will shape how FEs build expertise, demonstrate readiness, share what they know, and apply their capabilities with customers. This role owns a portfolio, not a single program. That portfolio may include skills verification, technical validation, role-based readiness paths, practical challenges, and new approaches we have not yet imagined. Your job is to understand where the field is headed, identify the capabilities that will matter most, and turn that insight into experiences and systems that help FEs grow and perform. This is a high-visibility, high-autonomy role for someone who wants to build. You will work with FE leaders, product and technical communities, regional teams, enablement partners, HR, and internal platform teams to define what “field-ready” means and make it useful in the flow of work. You will have the opportunity to influence how a global technical organization develops - and to create programs that become part of how Databricks operates. The best person for this role is equal parts strategist, product thinker, builder, and operator. You can see around corners, create structure from ambiguity, earn trust with senior stakeholders, and turn an idea into something the field actually uses. You are energized by the possibility of using AI not only as a topic to teach, but as a catalyst to redesign how capability is built, measured, and scaled. What You'll Do • Set the vision and roadmap for FE capability. Develop a clear point of view on how Databricks should build, demonstrate, recognize, and continuously evolve field expertise. Translate FE strategy, product priorities, customer needs, and the changing nature of technical work into a focused portfolio of investments. • Own and evolve a portfolio of readiness experiences. Bring together existing programs and new opportunities across skills verification, technical demonstrations, role-based pathways, credentials, and practical application. Decide what to scale, redesign, connect, or retire to keep the portfolio coherent and valuable. • Invent new ways for FEs to build and prove expertise. When the field needs a new capability, design the right experience - not automatically another course. This could be a customer scenario, a live technical demonstration, a peer review, a contribution model, an AI-enabled assessment, or something entirely new. Prototype quickly, learn from the field, and scale the strongest ideas. • Make readiness relevant to the work FEs actually do. Partner with practitioners, managers, product teams, and SME communities to define credible standards and evidence of capability. Embed development and validation into existing FE workflows wherever possible, making readiness a pull-based experience rather than an additional layer of process. • Help the organization adapt to an AI-enabled future. Stay close to how AI is changing FE workflows, technical depth, customer engagement, and delivery models. Ensure our capability models measure judgment, problem-solving, architecture, collaboration, and customer impact - not just static product knowledge. Experiment with AI to improve assessment quality, personalize development, surface expertise, and scale program operations responsibly. • Create the systems and signals that make capability visible. Partner with internal platform and engineering teams to t