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.
- 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.
- 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.
- Hands-on experience with attribution, incrementality testing, and/or marketing mix modeling, plus applied statistics.
- Knowledge of machine learning models, and the ability to help build and use them in production.
- Experience mentoring and developing others.
- Experience with Salesforce, Marketo, or similar GTM systems data.
- Experience across PLG, SLG, ABM, and Enterprise sales motions.
- Experience building natural language question-and-answer tools for business data.
- Privacy-first and cookieless measurement experience.
#LI-JM5
Compensation for this role is in the form of base salary. This role does not have a variable compensation component.
The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.
These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.
An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.
Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.
As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.
We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.
- Competitive pay based on the work you do here and not your previous salary
- Health coverage for you and your family in many locations
- Ability to craft your calendar with flexible locations and schedules for many roles
- Generous number of vacation days each year
- Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
- Up to 40 hours each year to use toward volunteer projects you love
- Embracing parenthood with minimum of 16 weeks of parental leave
Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.
We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email [email protected]. We will reply to your request within 24 business hours of submission.
Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster)
Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries’ export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.
Please see here for our Privacy Statement.
Skills Required
- Bachelor's degree or equivalent in Economics, Statistics, Engineering, Computer Science, or another quantitative or technical field
- 10+ years of experience in marketing or go-to-market analytics at a B2B company
- Experience designing data and analytics architecture and recommending tools or platforms to build, buy, or retire
- Experience building business cases covering cost, value, total cost of ownership, and resource requirements
- Experience influencing senior leaders and gaining agreement on recommendations
- Consultative approach with the ability to identify business problems and translate them into analysis plans
- Experience with funnel economics and performance modeling across sales and marketing data
- Experience with account-based strategy, marketing lifecycle analytics, and deal lifecycle analytics
- Strong presentation skills for explaining methods, trade-offs, and results to executives and nontechnical teams
- Extensive SQL, dbt or similar, data modeling, and cloud data warehouse experience, preferably BigQuery
- Python or R skills with clean, tested code
- Hands-on experience with attribution, incrementality testing, and/or marketing mix modeling
- Applied statistics experience
- Knowledge of machine learning models and ability to help build and use them in production
- Experience mentoring and developing others
- Experience with Salesforce, Marketo, or similar go-to-market systems data
- Experience across product-led growth, sales-led growth, account-based marketing, and enterprise sales motions
- Experience building natural-language question-and-answer tools for business data
- Privacy-first and cookieless measurement experience
Elastic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Elastic and has not been reviewed or approved by Elastic.
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Fair & Transparent Compensation — Pay is considered competitive across many technical and go‑to‑market roles and compares well within its peer group. Strong equity components and benefits bolster perceived total compensation.
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Healthcare Strength — Health coverage is described as fully paid for employees and families in many locations, which is unusually generous among tech firms. Comprehensive medical, dental, and vision coverage is emphasized in official materials.
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Parental & Family Support — A minimum of 16 weeks of paid parental leave is offered globally, with additional family‑formation support. These policies are positioned as core elements of the package.
Elastic Insights
What We Do
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.
Why Work With Us
Free and open isn’t just how we build our products, it’s how we build our culture. We value creativity and mobility, so you can grow how (and where) you want to… and be happier at work.
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