Jobs / United States / Elasticsearch INC

Elasticsearch INC

Principal, Marketing Analytics

United States Posted today

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Skills this job asks for

Machine learningComplianceStatisticsB2B salesSQLdbtWarehouse operationsPython

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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 20 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.
  • 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.
  • What Elasticsearch INC paid sponsored hires in similar roles2 certified filings for “Senior Product Marketing Manager” (Marketing Managers) in WA: $205k–$205k, median $205k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 20 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-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 Elasticsearch INC paid sponsored hires in similar roles
2 certified filings for “Senior Product Marketing Manager” (Marketing Managers) in WA: $205k–$205k, median $205k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

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.

About the role

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What Is The Role: We are looking for a Principal who understands how marketing and sales work collectively to create revenue. You’ll be the architect, the builder, and the link between the business and the systems that serve it. You’ll learn what decisions leaders face, form a point of view on which systems, tools, and products are worth building or buying, and make the case for it with clear reasoning. You’ll also build the data models and analysis that deliver the value. You’ll partner with Marketing, Sales, Revenue Operations, Finance, and Data teams, and you’ll mentor senior analysts and engineers. Your role is to help the business answer where to invest, which accounts to pursue, and what drives revenue. • Meet with business leaders to understand their problems and decisions. Turn them into analyses, recommended actions, and clear requirements for systems and data. • Recommend which systems, tools, and products to prioritize, with a clear point of view and the reasoning behind it. • Build the business case for each investment: expected value, required resources, and total cost of ownership. Present it to leaders and gain agreement. • Design the overall architecture for marketing and sales measurement, and build the core data models, pipelines, and machine learning datasets, with testing and version control. • Build models that show how marketing spend and activity convert to pipeline and revenue, and measure the full customer path from first touch to closed deal. • Define account-based performance measures and apply them with Sales and Marketing. • Combine attribution, incrementality, and mix modeling into one consistent view of what works. • Build tools that let marketers ask questions in plain language and get trusted answers. • Set standards for metric definitions, data quality, and privacy compliance (GDPR/CCPA), and keep them consistent across Sales, Marketing, and systems teams. • Plan roadmaps and milestones with Data Engineering, Analytics, and IT. • Mentor senior analysts and engineers. What You Bring: • Bachelor’s degree or equivalent in a quantitative or technical field, such as Economics, Statistics, Engineering, or Computer Science. • 10+ years in marketing or GTM analytics at a B2B company. • Experience designing data and analytics architecture, and recommending which tools and platforms to build, buy, or retire. • Experience building business cases, including cost, value, and total cost of ownership, and influencing senior leaders to reach agreement. • A consultative style. You can uncover business pain points and turn them into analysis plans that lead to decisions. • Funnel economics and performance modeling experience across sales and marketing data. • Experience with account-based strategy, motions, and frameworks, and with marketing lifecycle and deal lifecycle analytics. • Proficient presentation skills, with the ability to explain methods, trade-offs, and results to executives and non-technical teams. • Extensive SQL and dbt (or similar), data modeling, and cloud data warehouse experience, preferably BigQuery. • Python or R skills, with clean, tested code. •

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