Datadog

Datadog

Enterprise Sales Executive (SLED)

Washington, USA, Remote · Mid

Sponsorship not specified$110k-$120kDetected 14 days ago
DatadogAccessibilitySalesForecastingCollaboration

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odds of building a lasting career here

53Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level II)66
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~30% per draw at Level II). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card follow-through: 100%

Of 8 labor certifications old enough to have been used, 0 expired without the employer filing the next step. Median time from filing to decision: 486 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

15 transfer filings in the last year, covering 15 workers. Median labor-condition decision: 8 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

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About the role

  • Sellers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product.
  • Whether you're looking to learn from the best or be the best, the Datadog sales team is dedicated to furthering personal development and team success.
  • This is a lucrative opportunity to break into new State, Local, and Education accounts within a rich territory, as well work with accounts who are in a hybrid state and transitioning to the cloud.

Responsibilities

  • Maintain, build and own specific relationship maps for your territory including existing relationships and aspirational contacts
  • Develop a deep comprehension of customer's business
  • Able to demonstrate methodology to prospect and build pipeline on your own

Requirements

  • Someone with 3+ years closing experience (mix of field selling within mid-market or enterprise)

Nice to have

  • Experienced in working for an innovative tech company (SaaS, IT infrastructure or similar preferred)

Compensation

  • $110,000 - $120,000 USD

Benefits

  • New hire stock equity (RSU) and employee stock purchase plan (ESPP)
  • Generous and competitive medical benefits package
  • Retirement savings match
  • Datadog offers a competitive salary and equity package, and may include variable compensation.
  • Prospect into State, Local, and Education organizations while running an efficient sales process
  • Experienced in selling into state, local, and education organizations with the ability to win new logos
  • Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center.

Company info

  • Our SLED sales team works with a best-of-breed product that solves real problems for our customers.
  • It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers.
  • Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale.

Equal opportunity

  • Equal Opportunity at Datadog:
  • This form is for accommodation requests only and cannot be used to inquire about the status of applications.

Visa & Work Authorization

  • t opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics

This listing is sourced directly from Datadog's careers page and normalized into a canonical job model.