Synced from Greenhouse · Oct 22

Principal, Marketing Analytics

ElasticUnited StatesPosted Oct 22, 2026
Analytics ManagerPrincipal
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Mirrored from Elastic's own Greenhouse careers system · refreshed hourly

$160k–$253k
Compensation
401
Other open Elastic roles
Oct 22
Posted
Greenhouse
Applicant system
Job descriptionReq 8281506

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.
  • 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.
Bonus Points:
  • 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.

The typical starting salary range for this role is:
$159,800—$252,800 USD
The typical starting salary range for this role in the select locations listed above is:
$191,900—$303,500 USD

Additional Information - We Take Care of Our People

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 candidate_accessibility@elastic.co. 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.

View original posting on Greenhouse

What applying to Elastic usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Elastic can typically expect a standard structured hiring workflow common to this platform. After submitting an application, candidates may receive an automated confirmation, and response times vary depending on the role and team. The process commonly includes an initial recruiter screen, followed by one or more interviews with hiring managers or team members, which may include multiple stages such as technical assessments, case studies, or panel discussions depending on the position. Communication is often conducted via email through the Greenhouse system, and candidates may be able to track general application status through a candidate portal. Overall, applicants should prepare for a methodical, multi-step evaluation process that can vary in length and structure based on department and seniority level.

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Principal, Marketing Analytics
Elastic · United States
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